March 13, 2009 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION

Size: px
Start display at page:

Download "March 13, 2009 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION"

Transcription

1 March 13, 2009 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 1. Parial Derivaives and Differeniable funcions In all his chaper, D will denoe an open subse of R n. Definiion 1.1. Consider a funcion f : D R and le p D, i = 1,, n. We define he parial derivaive of f wih respec o he i-h variable a he poin p as he following limi (if i exiss) f(p + e i ) f(p) (p) i 0 where {e 1,..., e n } is he canonical basis of R n, defined as follows e i = (0,..., 0, i, 0,..., 0 ) }{{}}{{} i 1 erms n i erms For example, in R 2 he canonical basis is and in R 3 he canonical basis is e 1 = (1, 0) e 2 = (0, 1) e 1 = (1, 0, 0) e 2 = (0, 1, 0) e 3 = (0, 0, 1) Remark 1.2. When n = 2, in he above definiion we le we and use he noaion, Likewise, when n = 3, we le and use he noaion, p = (x, y), f(x, y) : R 2 R f(x +, y) f(x, y) (x, y) 0 (x, y) 0 (x, y, z) 0 (x, y, z) 0 f(x, y + ) f(x, y) p = (x, y, z) f(x +, y, z) f(x, y, z) (x, y, z) 0 f(x, y +, z) f(x, y, z) f(x, y, z + ) f(x, y, z) 1

2 2 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION Example 1.3. In Economics, he parial derivaives of a uiliy funcion are called marginal uiliies, he parial derivaives of a producion funcion are called marginal producs. Consider, for example he Cobb-Douglas producion funcion f(k, L) = 5K 1/3 L 2/3 where f is he number of unis produced, K is he capial and L is labor. Tha is, he above formula means ha if we use K unis of capial and L unis of labor, hen we produce f(k, L) = 5K 1/3 L 2/3 unis of a good. The consans A = 5, α = 1/3 and β = 2/3 are echnological parameers. The marginal producs wih respec o capial and labor are The marginal produc of labor, K = 5 3 K 2/3 L 2/3 L = 10 3 K1/3 L 1/3 (K, L) L is inerpreed in Economics as an approximaion o he variaion in he producion of he good when we are using K unis of capial and L unis of labor and we swich o use an addiional uni L + 1 of labor and he same unis K of capial as before. We see ha he marginal produc of labor and capial is posiive. Tha is, if we use more labor and/or more capial, producion increases. On he oher hand, he marginal produc of labor is decreasing in labor and increasing in capial. We may inerpre his as follows. Suppose ha we keep consan he amoun of capial ha we are using K. If L > L hen f(k, L + 1) f(k, L ) < f(k, L + 1) f(k, L) Tha is, an increase in he producion when we use an addiional uni of labor is decreasing in he iniial labor ha is being used. If we keep he capial consan, using on addiional uni of labor, if we are already using a lo of labor, does no increase much he producion. We may imagine ha f(k, L) is he producion of a farm produc in a piece of land where L is he number of he workers and he size K of he land is consan. The impac in he producion when hiring and addiional person is greaer if few people are working in he land as compared wih he case in which we already have a lo of people working in he land. Suppose ha he amoun of labor L is kep consan. If K > K hen f(k, L + 1) f(k, L) > f(k, L + 1) f(k, L) Tha is, he increase in he producion when we use one addiional uni of labor is larger he more capial we use. Capial and labor are complemenary. In he previous example, hiring and addiional worker has a larger effec on he producion he larger is he size of land.

3 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 3 Definiion 1.4. Consider a funcion f : D R. Le p D and suppose all he parial derivaives (p), (p),, (p) 1 2 n exis a he poin p. We define he gradien of f a p as he following vecor ( f(p) = (p), (p),, ) (p) 1 2 n Definiion 1.5. Consider a funcion f : D R. Le p D and suppose all he parial derivaives (p), (p),, (p) 1 2 n exis a he poin p. We say ha f is differeniable a p if Noe ha he limi is aken for v R n. f(p + v) f(p) f(p) v lim = 0 v 0 v Remark 1.6. A funcion of wo variables f : D R 2 is differeniable a he poin p = (a, b) if Leing f(a + v 1, b + v 2 ) f(a, b) f(a, b) (v 1, v 2 ) lim = 0 (v 1,v 2) (0,0) (v 1, v 2 ) x = a + v 1, y = b + v 2 we see ha (v 1, v 2 ) (0, 0) is equivalen o (x, y) (a, b), so we may wrie his limi as f(x, y) f(a, b) f(a, b) (x a, y b) lim = 0 (x,y) (a,b) (x a, y b) Wriing his limi explicily we wee ha f is differeniable a he poin p = (a, b) if (1.1) lim (x,y) (a,b) f(x, y) f(a, b) (a, b) (x a) (a, b) (y b) = 0 (x a)2 + (y b) 2 Example 1.7. Consider he funcion { xy 2 f(x, y) = x 2 +y if (x, y) (0, 0), 2 0 if (x, y) = (0, 0). We will show ha f is no differeniable a he poin p = (0, 0). Firs of all, we compue f(0, 0). Noe ha f(, 0) f(0, 0) (0, 0) 0 (0, 0) 0 f(0, ) f(0, 0) = = 0

4 4 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION so, f(0, 0) = (0, 0). Le us use he noaion v = (x, y). Then, f is differeniable a he poin p = (0, 0) if and only if f(p + v) f(p) f(p) v 0 v 0 v f ((0, 0) + (x, y)) f(0, 0) f(p) (x, y) x2 + y 2 f(x, y) f(0, 0) (0, 0) (x, y) x2 + y 2 f(x, y) x2 + y 2 xy 2 We prove ha he above limi does no exis. Consider he funcion xy 2 g(x, y) = Noe ha and noe ha so he limi 0 lim g(, 0) 0 0 (2 2 ) = 0 3/2 3 lim g(, ) 0 0 (2 2 ) = 1 3/2 (2) 0 3/2 lim xy 2 does no exis and we conclude ha f is no differeniable a he poin (0, 0). Example 1.8. Consider now he funcion { xy 3 f(x, y) = x 2 +y if (x, y) (0, 0), 2 0 if (x, y) = (0, 0). We will show ha f is differeniable a he poin p = (0, 0). Firs of all, we compue f(0, 0). Noe ha (0, 0) 0 f(, 0) f(0, 0) (0, 0) 0 f(0, ) f(0, 0) = = 0

5 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 5 so, f(0, 0) = (0, 0). Le us use he noaion v = (x, y). Then, f is differeniable a he poin p = (0, 0) if and only if f(p + v) f(p) f(p) v 0 v 0 v f((0, 0) + (x, y)) f(0, 0) f(p) (x, y) x2 + y 2 f(x, y) f(0, 0) (0, 0) (x, y) x2 + y 2 f(x, y) x2 + y 2 xy 3 Le ε > 0. Take δ = ε and suppose ha 0 < x 2 + y 2 < δ. Then, xy 3 = x y2 y x2 y 2 y = x2 + y ( 2 x 2 + y 2) y ( x 2 + y 2) 3/2 y = So, lim = y x 2 + y 2 < δ = ε xy 3 = 0 and he funcion is differeniable a he poin (0, 0). Proposiion 1.9. Le f : D R. If f is differeniable a some poin p D, hen f is coninuous a ha poin. Example Consider he funcion { x 3 y f(x, y) = x 4 +y if (x, y) (0, 0), 2 0 if (x, y) = (0, 0). Is i coninuous and/or differeniable a (0, 0)? One compues easily he ieraed limi ( ) lim lim f(x, y) = 0 x 0 y 0 On he oher hand, aking he curve x() =, y() = 2

6 6 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION we see ha So, lim f(, ) = lim f(x, y) does no exis. I follows ha f is no coninuous a (0, 0). In addiion, by Proposiion 1.9, f is no differeniable a (0, 0), eiher. Theorem Le f : D R and p D. Suppose ha here is some r > 0 such ha he parial derivaives, 1,,, 2 n exis a every poin of he open ball B(p, r) and are coninuous funcions on ha ball. Then, he funcion f is differeniable a p. Example The previous Theorem applies o show ha he funcion is differeniable a every poin of R 2. f(x, y, z) = xe yz + y sin z Definiion A funcion f : D R is of class C 1 in D if all he parial derivaives of f exis and are coninuous funcions on D. In his case we wrie f C 1 (D). 2. Direcional derivaives Definiion 2.1. Le f : D R n R. Fix a poin p D and a vecor v R n. If he following limi exiss D v f(p) 0 f(p + v) f(p) i is called he derivaive of f a p along (he vecor) v. If v = 1, hen D v f(p) is called he direcional derivaive of f a p in he direcion of (he vecor) v Remark 2.2. Le n = 1. Le f : R R, p R and v = 1. The above definiion coincides wih he derivaive of a one variable funcion f f(p + ) f(p) (p) 0 Example 2.3. Le f : R 2 R be defined by f(x, y) = xy and ake p = (1, 1), v = (3, 4). Then, for R we have ha so, p + v = (1 + 3, 1 + 4) f(1 + 3, 1 + 4) f(1, 1) D v f(p) 0 (1 + 3)( 1 + 4) + 1 = 1 0

7 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 7 And, since v = = 5, he direcional derivaive of f a p in he direcion of v is 1 v D vf(p) = 1 5 Remark 2.4. If we ake v = e i = (0,..., 0, }{{} 1, 0,..., 0) i o be he i h vecor of he canonical basis, hen D ei f(p) = i (p) is he i h parial derivaive of f a he poin p. Proposiion 2.5. Le f : D R be differeniable a he poin p D. Then, (2.1) D v f(p) = f(p) v Example 2.6. As in Example 2.3, le f : R 2 R be defined by f(x, y) = xy and ake p = (1, 1), v = (3, 4). Then, f(p) = (y, x) x=1 y= 1 = ( 1, 1) and, since f is differeniable on all of R 2, we have ha as compued in Example 2.3. D v f(p) = f(p) v = ( 1, 1) (3, 4) = = 1 Remark 2.7. One may also define he derivaive of a funcion f : D R n R m along (he vecor) v. To do so, we wrie he funcion f using is coordinae funcions f(x) = (f 1 (x), f 2 (x),, f m (x)) wih f i : D R for each i = 1,, m. And define D v f(p) = (D v f 1 (p), D v f 2 (p),, D v f m (p)) We see now ha D v f(p) is a vecor in R m. Likewise we may define he direcional derivaive of f a he poin p in he direcion of a uniary vecor u. 3. inerpreaion of he gradien The formula 2.1 may be used o give an inerpreaion of he gradien as follows. Recall ha given wo vecors u, v in R n, heir scalar produc saisfies u v = u v cos θ where θ is he angle beween he wo vecors.

8 8 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION u θ Applying his observaion o formula 2.1, we see ha v D v f(p) = f(p) v = f(p) v cos θ where θ is he angle beween he vecors f(p) and v. Taking v o be uniary, we see ha he derivaive of f in he direcion of v is D v f(p) = f(p) cos θ Thus, D v f(p) aains a maximum when θ = 0, ha is, when he vecors f(p) and v poin in he same direcion. aains a minimum when θ = π, ha is, when he vecors f(p) and v poin in he opposie direcions. is zero when θ = π/2 or θ = 3π/2, ha is, when he vecors f(p) and v are perpendicular. I follows ha, The funcion f grows he fases in he direcion of f(p). The funcion f decreases he fases in he direcion opposie o f(p). The funcion f remains consan in he direcions perpendicular o f(p). D f(p) = 4. The chain rule Definiion 4.1. Given a funcion f(x) = (f 1 (x), f 2 (x),, f m (x)) : D R n R m and a poin p D, we define he Jacobian marix of f a he poin p as he following marix of order m n 1(p) 2 1(p) n 2(p) 2 1(p) 1 2(p) 1. m(p) 1.. m(p) 2 2(p) n. m(p) n Remark 4.2. If f(x) = D R n R Wha is he difference beween D f(p) and f(p)? Remark 4.3. If m = n = 1 Wha is D f(p)? Definiion 4.4. A funcion f(x) = (f 1 (x), f 2 (x),, f m (x)) : D R n R m is said o be differeniable a a poin p D if each of he funcions f 1 (x), f 2 (x),, f m (x) is differeniable a p. Theorem 4.5 (The chain rule). Le g : R n R m and f : R m R l. Suppose ha g is differeniable a p R n and ha f is differeniable a g(p) R m. Then, he funcion f g is differeniable a p and D(f g)(p) = D f(g(p)) D g(p)

9 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 9 Remark 4.6. The expression D(f g)(p) = D f(g(p)) D g(p) conains he produc of 2 marices. Example 4.7 (Special case of he chain rule). Le σ : R R 2 and f : R 2 R be differeniable. Suppose ha σ() may be wrien as Then, he chain rule says ha σ() = (x(), y()) d f(x(), y()) = D(f σ)() = D f(x, y) x=x() D σ() ( ) ( ) = x=x() x () y () = (x(), y())x () + (x(), y())y () Example 4.8 (Special case of he chain rule). Le g(s, ) : R 2 R 2 and f(x, y) : R 2 R be differeniable. Suppose ha g(s, ) may be wrien as so ha hen, he chain rule says ha g(s, ) = (x(s, ), y(s, )) (f g)(s, ) = f(g(s, )) = f (x(s, ), y(s, )) D f (x(s, ), y(s, )) = D(f g)(s, ) = D f(x, y) x=x(s,) D g(s, ) = = ( ) ( ( s + s s s ) y=y(s,) + ) Tha is, (f g) s (f g) = s + = + s Example 4.9. Consider he Cobb-Douglas producion funcion f(k, L) = 5K 1/3 L 2/3 where f are he unis produced, K is capial and L is labor. Suppose ha capial and labor change wih ime K = K(), L = L() Then he producion funcion f(k(), L())

10 10 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION is also a funcion of ime. Wha is he rae of change of he producion a a given ime? We may answer his quesion using he chain rule. df(k(), L()) = dk K + dl L = 5 3 K 2/3 L 2/3 dk K1/3 1/3 dl L Example Suppose an agen has he following differeniable uiliy funcion u(x, y) where x is a consumpion good and y is air polluion. Then, he uiliy of he agen is increasing in x and decreasing in y, u > 0 u < 0 Suppose ha he producion of x unis of he good generaes y = f(x) unis of polluion, Wha is he opimal level of consumpion of x? The uiliy of he agen when he consumes x unis of he good and y = f(x) unis of polluion are generaed is u(x, f(x)) The agens maximizes his uiliy funcion. The firs order condiion is du(x, f(x)) = 0 dx using he chain rule we obain ha he equaion 0 = u u (x, f(x)) + (x, f(x))f (x) deermines he opimal level of producion of he good. 5. Derivaive along a curve and level surfaces Remark 5.1 (A special case of he chain rule). Le σ : R R n be a differeniable curve and le f : D R be differeniable, where D is an open subse of R n. Suppose, σ() can be wrien as where each σ() = (σ 1 (), σ 2 (),..., σ n ()) dσ i () is differeniable for every i = 1,..., n and every R. Hence, we may wrie dσ = Then, f(σ()) is differeniable and ( dσ1, dσ 2,..., dσ n d dσ f(σ()) = f(σ()) )

11 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION 11 Example 5.2. If f : R 2 R is a funcion of wo variables and x = x(), y = y(), he chain rule is d (x, y) f(x(), y()) = dx() (x, y) + dy() x=x() x=x() Example 5.3. If f : R 3 R is a funcion of hree variables and x = x(), y = y(), z = z(), he chain rule is d (x, y, z) f(x(), y(), z()) = dx() (x, y, z) + dy() + x=x() z=z() x=x() z=z() Remark 5.1 provides anoher inerpreaion of he gradien. Le p D and le f : D R be differeniable, where D is some open subse of R n. Le C R and suppose he level surface S C = {x D : f(x) = C} is no empy. Le σ : R R n be a differeniable curve and suppose ha σ() S C for all R. Tha is f(σ()) = c for every R. Differeniaing and using he above chain rule we have ha 0 = d dσ f(σ()) = f(σ()) Tha is f(σ()) and dσ()/ are perpendicular for every R. (x, y, z) z x=x() z=z() dz() f(p) σ () p {x: f (x) = C} The above argumen shows ha a any poin p S C, he gradien f(p) is perpendicular o he surface level S C. Remark 5.4. Le us compue he plane angen o he graph of a funcion of wo variables. To do his, consider a differeniable funcion f : R 2 R. The graph of f is he se G = {(x, y, f(x, y)) : (x, y) R 2 }

12 12 CHAPTER 3: PARTIAL DERIVATIVES AND DIFFERENTIATION Fix a poin p = (a, b) R 2. Consider he following funcion of hree variables Then,he graph of f may be wrien as g(x, y, z) = f(x, y) z G = {(x, y, z) R 3 : g(x, y, z) = 0} Then, he plane T angen o G a he poin (a, b, f(a, b)) saisfies he wo following properies T conains he poin (a, b, f(a, b)). T is perpendicular o he gradien g(a, b, f(a, b)). This informaion permis us o compue he equaions for T as follows. Firs of all, i follows ha an equaion for T is g(a, b, f(a, b)) ((x, y, z) (a, b, f(a, b))) = 0 and noe ha ( ) g(a, b, f(a, b)) = (a, b), (a, b), 1 Hence, an equaion for T is he following (5.1) f(a, b) + (a, b) (x a) + (a, b) (y b) = z We may use he above o provide anoher inerpreaion of he definiion of differeniabiliy 1.5. Le P 1 (x, y) = f(a, b) + (a, b) (x a) + (a, b) (y b) For he case of a funcion of wo variables, Equaion 1.1 says ha he funcion f is differeniable a he poin (a, b) if f(x, y) P 1 (x, y) lim = 0 (x,y) (a,b) (x a, y b) In view of Equaion 5.1, he funcion f is differeniable a he poin (a, b) if he angen plane is a good approximaion o he value of he funcion f(x, y) f(a, b) + (a, b) (x a) + (a, b) (y b)

Technology. Production functions Short run and long run Examples of technology Marginal product Technical rate of substitution Returns to scale

Technology. Production functions Short run and long run Examples of technology Marginal product Technical rate of substitution Returns to scale Technology Producion funcions Shor run and long run Examples of echnology Marginal produc Technical rae of subsiuion Reurns o scale Analogies wih Consumer Theory Consumers Firms Maximize uiliy Maximize

More information

Revision: June 11, E Main Suite D Pullman, WA (509) Voice and Fax

Revision: June 11, E Main Suite D Pullman, WA (509) Voice and Fax 2.5.3: Sinusoidal Signals and Complex Exponenials Revision: June 11, 2010 215 E Main Suie D Pullman, W 99163 (509) 334 6306 Voice and Fax Overview Sinusoidal signals and complex exponenials are exremely

More information

EE201 Circuit Theory I Fall

EE201 Circuit Theory I Fall EE1 Circui Theory I 17 Fall 1. Basic Conceps Chaper 1 of Nilsson - 3 Hrs. Inroducion, Curren and Volage, Power and Energy. Basic Laws Chaper &3 of Nilsson - 6 Hrs. Volage and Curren Sources, Ohm s Law,

More information

Section 14.3 Partial Derivatives

Section 14.3 Partial Derivatives Section 14.3 Partial Derivatives Ruipeng Shen March 20 1 Basic Conceptions If f(x, y) is a function of two variables x and y, suppose we let only x vary while keeping y fixed, say y = b, where b is a constant.

More information

Lecture #7: Discrete-time Signals and Sampling

Lecture #7: Discrete-time Signals and Sampling EEL335: Discree-Time Signals and Sysems Lecure #7: Discree-ime Signals and Sampling. Inroducion Lecure #7: Discree-ime Signals and Sampling Unlike coninuous-ime signals, discree-ime signals have defined

More information

FUNCTIONS OF SEVERAL VARIABLES AND PARTIAL DIFFERENTIATION

FUNCTIONS OF SEVERAL VARIABLES AND PARTIAL DIFFERENTIATION FUNCTIONS OF SEVERAL VARIABLES AND PARTIAL DIFFERENTIATION 1. Functions of Several Variables A function of two variables is a rule that assigns a real number f(x, y) to each ordered pair of real numbers

More information

4.5 Biasing in BJT Amplifier Circuits

4.5 Biasing in BJT Amplifier Circuits 4/5/011 secion 4_5 Biasing in MOS Amplifier Circuis 1/ 4.5 Biasing in BJT Amplifier Circuis eading Assignmen: 8086 Now le s examine how we C bias MOSFETs amplifiers! f we don bias properly, disorion can

More information

Negative frequency communication

Negative frequency communication Negaive frequency communicaion Fanping DU Email: dufanping@homail.com Qing Huo Liu arxiv:2.43v5 [cs.it] 26 Sep 2 Deparmen of Elecrical and Compuer Engineering Duke Universiy Email: Qing.Liu@duke.edu Absrac

More information

Definitions and claims functions of several variables

Definitions and claims functions of several variables Definitions and claims functions of several variables In the Euclidian space I n of all real n-dimensional vectors x = (x 1, x,..., x n ) the following are defined: x + y = (x 1 + y 1, x + y,..., x n +

More information

11.2 LIMITS AND CONTINUITY

11.2 LIMITS AND CONTINUITY 11. LIMITS AND CONTINUITY INTRODUCTION: Consider functions of one variable y = f(x). If you are told that f(x) is continuous at x = a, explain what the graph looks like near x = a. Formal definition of

More information

Lab 3 Acceleration. What You Need To Know: Physics 211 Lab

Lab 3 Acceleration. What You Need To Know: Physics 211 Lab b Lab 3 Acceleraion Wha You Need To Know: The Physics In he previous lab you learned ha he velociy of an objec can be deermined by finding he slope of he objec s posiion vs. ime graph. x v ave. = v ave.

More information

FROM ANALOG TO DIGITAL

FROM ANALOG TO DIGITAL FROM ANALOG TO DIGITAL OBJECTIVES The objecives of his lecure are o: Inroduce sampling, he Nyquis Limi (Shannon s Sampling Theorem) and represenaion of signals in he frequency domain Inroduce basic conceps

More information

[f(t)] 2 + [g(t)] 2 + [h(t)] 2 dt. [f(u)] 2 + [g(u)] 2 + [h(u)] 2 du. The Fundamental Theorem of Calculus implies that s(t) is differentiable and

[f(t)] 2 + [g(t)] 2 + [h(t)] 2 dt. [f(u)] 2 + [g(u)] 2 + [h(u)] 2 du. The Fundamental Theorem of Calculus implies that s(t) is differentiable and Midterm 2 review Math 265 Fall 2007 13.3. Arc Length and Curvature. Assume that the curve C is described by the vector-valued function r(r) = f(t), g(t), h(t), and that C is traversed exactly once as t

More information

Figure A linear pair? Explain. No, because vertical angles are not adjacent angles, and linear pairs are.

Figure A linear pair? Explain. No, because vertical angles are not adjacent angles, and linear pairs are. Geomery Review of PIL KEY Name: Parallel and Inersecing Lines Dae: Per.: PIL01: Use complemenary supplemenary and congruen o compare wo angles. 1) Complee he following definiion: Two angles are Complemenary

More information

Math 5BI: Problem Set 1 Linearizing functions of several variables

Math 5BI: Problem Set 1 Linearizing functions of several variables Math 5BI: Problem Set Linearizing functions of several variables March 9, A. Dot and cross products There are two special operations for vectors in R that are extremely useful, the dot and cross products.

More information

CHAPTER 11 PARTIAL DERIVATIVES

CHAPTER 11 PARTIAL DERIVATIVES CHAPTER 11 PARTIAL DERIVATIVES 1. FUNCTIONS OF SEVERAL VARIABLES A) Definition: A function of two variables is a rule that assigns to each ordered pair of real numbers (x,y) in a set D a unique real number

More information

Review guide for midterm 2 in Math 233 March 30, 2009

Review guide for midterm 2 in Math 233 March 30, 2009 Review guide for midterm 2 in Math 2 March, 29 Midterm 2 covers material that begins approximately with the definition of partial derivatives in Chapter 4. and ends approximately with methods for calculating

More information

Functions of several variables

Functions of several variables Chapter 6 Functions of several variables 6.1 Limits and continuity Definition 6.1 (Euclidean distance). Given two points P (x 1, y 1 ) and Q(x, y ) on the plane, we define their distance by the formula

More information

MATH 8 FALL 2010 CLASS 27, 11/19/ Directional derivatives Recall that the definitions of partial derivatives of f(x, y) involved limits

MATH 8 FALL 2010 CLASS 27, 11/19/ Directional derivatives Recall that the definitions of partial derivatives of f(x, y) involved limits MATH 8 FALL 2010 CLASS 27, 11/19/2010 1 Directional derivatives Recall that the definitions of partial derivatives of f(x, y) involved limits lim h 0 f(a + h, b) f(a, b), lim h f(a, b + h) f(a, b) In these

More information

EE 330 Lecture 24. Amplification with Transistor Circuits Small Signal Modelling

EE 330 Lecture 24. Amplification with Transistor Circuits Small Signal Modelling EE 330 Lecure 24 Amplificaion wih Transisor Circuis Small Signal Modelling Review from las ime Area Comparison beween BJT and MOSFET BJT Area = 3600 l 2 n-channel MOSFET Area = 168 l 2 Area Raio = 21:1

More information

OpenStax-CNX module: m Elemental Signals. Don Johnson. Perhaps the most common real-valued signal is the sinusoid.

OpenStax-CNX module: m Elemental Signals. Don Johnson. Perhaps the most common real-valued signal is the sinusoid. OpenSax-CNX module: m0004 Elemenal Signals Don Johnson This work is produced by OpenSax-CNX and licensed under he Creaive Commons Aribuion License.0 Absrac Complex signals can be buil from elemenal signals,

More information

Lecture 4. EITN Chapter 12, 13 Modulation and diversity. Antenna noise is usually given as a noise temperature!

Lecture 4. EITN Chapter 12, 13 Modulation and diversity. Antenna noise is usually given as a noise temperature! Lecure 4 EITN75 2018 Chaper 12, 13 Modulaion and diversiy Receiver noise: repeiion Anenna noise is usually given as a noise emperaure! Noise facors or noise figures of differen sysem componens are deermined

More information

Solutions to the problems from Written assignment 2 Math 222 Winter 2015

Solutions to the problems from Written assignment 2 Math 222 Winter 2015 Solutions to the problems from Written assignment 2 Math 222 Winter 2015 1. Determine if the following limits exist, and if a limit exists, find its value. x2 y (a) The limit of f(x, y) = x 4 as (x, y)

More information

Parametrizations of curves on a plane (Sect. 11.1)

Parametrizations of curves on a plane (Sect. 11.1) Paramerizaions of curves on a plane (Sec..) Review: Curves on he plane. Parameric equaions of a curve. s of curves on he plane. The ccloid. Review: Curves on he plane Remarks: Curves on a plane can be

More information

f t 2cos 2 Modulator Figure 21: DSB-SC modulation.

f t 2cos 2 Modulator Figure 21: DSB-SC modulation. 4.5 Ampliude modulaion: AM 4.55. DSB-SC ampliude modulaion (which is summarized in Figure 21) is easy o undersand and analyze in boh ime and frequency domains. However, analyical simpliciy is no always

More information

i + u 2 j be the unit vector that has its initial point at (a, b) and points in the desired direction. It determines a line in the xy-plane:

i + u 2 j be the unit vector that has its initial point at (a, b) and points in the desired direction. It determines a line in the xy-plane: 1 Directional Derivatives and Gradients Suppose we need to compute the rate of change of f(x, y) with respect to the distance from a point (a, b) in some direction. Let u = u 1 i + u 2 j be the unit vector

More information

MATH 105: Midterm #1 Practice Problems

MATH 105: Midterm #1 Practice Problems Name: MATH 105: Midterm #1 Practice Problems 1. TRUE or FALSE, plus explanation. Give a full-word answer TRUE or FALSE. If the statement is true, explain why, using concepts and results from class to justify

More information

Communication Systems. Department of Electronics and Electrical Engineering

Communication Systems. Department of Electronics and Electrical Engineering COMM 704: Communicaion Lecure : Analog Mulipliers Dr Mohamed Abd El Ghany Dr. Mohamed Abd El Ghany, Mohamed.abdel-ghany@guc.edu.eg nroducion Nonlinear operaions on coninuous-valued analog signals are ofen

More information

Signal Characteristics

Signal Characteristics Signal Characerisics Analog Signals Analog signals are always coninuous (here are no ime gaps). The signal is of infinie resoluion. Discree Time Signals SignalCharacerisics.docx 8/28/08 10:41 AM Page 1

More information

10. The Series Resistor and Inductor Circuit

10. The Series Resistor and Inductor Circuit Elecronicsab.nb 1. he Series esisor and Inducor Circui Inroducion he las laboraory involved a resisor, and capacior, C in series wih a baery swich on or off. I was simpler, as a pracical maer, o replace

More information

MODELING OF CROSS-REGULATION IN MULTIPLE-OUTPUT FLYBACK CONVERTERS

MODELING OF CROSS-REGULATION IN MULTIPLE-OUTPUT FLYBACK CONVERTERS MODELING OF CROSS-REGULATION IN MULTIPLE-OUTPUT FLYBACK CONVERTERS Dragan Maksimovićand Rober Erickson Colorado Power Elecronics Cener Deparmen of Elecrical and Compuer Engineering Universiy of Colorado,

More information

MATH 12 CLASS 9 NOTES, OCT Contents 1. Tangent planes 1 2. Definition of differentiability 3 3. Differentials 4

MATH 12 CLASS 9 NOTES, OCT Contents 1. Tangent planes 1 2. Definition of differentiability 3 3. Differentials 4 MATH 2 CLASS 9 NOTES, OCT 0 20 Contents. Tangent planes 2. Definition of differentiability 3 3. Differentials 4. Tangent planes Recall that the derivative of a single variable function can be interpreted

More information

Section 15.3 Partial Derivatives

Section 15.3 Partial Derivatives Section 5.3 Partial Derivatives Differentiating Functions of more than one Variable. Basic Definitions In single variable calculus, the derivative is defined to be the instantaneous rate of change of a

More information

The University of Melbourne Department of Mathematics and Statistics School Mathematics Competition, 2013 JUNIOR DIVISION Time allowed: Two hours

The University of Melbourne Department of Mathematics and Statistics School Mathematics Competition, 2013 JUNIOR DIVISION Time allowed: Two hours The Universiy of Melbourne Deparmen of Mahemaics and Saisics School Mahemaics Compeiion, 203 JUNIOR DIVISION Time allowed: Two hours These quesions are designed o es your abiliy o analyse a problem and

More information

UNIT IV DIGITAL MODULATION SCHEME

UNIT IV DIGITAL MODULATION SCHEME UNI IV DIGIAL MODULAION SCHEME Geomeric Represenaion of Signals Ojecive: o represen any se of M energy signals {s i (} as linear cominaions of N orhogonal asis funcions, where N M Real value energy signals

More information

An off-line multiprocessor real-time scheduling algorithm to reduce static energy consumption

An off-line multiprocessor real-time scheduling algorithm to reduce static energy consumption An off-line muliprocessor real-ime scheduling algorihm o reduce saic energy consumpion Firs Workshop on Highly-Reliable Power-Efficien Embedded Designs Shenzhen, China Vincen Legou, Mahieu Jan, Lauren

More information

Lecture 19: Lowpass, bandpass and highpass filters

Lecture 19: Lowpass, bandpass and highpass filters Leure 9: Lowpass, bandpass and higass filers UHTXHQF\6HOHFLYH LOHUV Ideal frequeny-seleive filers are filers ha le frequeny omponens over a given frequeny band (he passband pass hrough undisored, while

More information

Unit 7 Partial Derivatives and Optimization

Unit 7 Partial Derivatives and Optimization Unit 7 Partial Derivatives and Optimization We have learned some important applications of the ordinary derivative in finding maxima and minima. We now move on to a topic called partial derivatives which

More information

Differentiable functions (Sec. 14.4)

Differentiable functions (Sec. 14.4) Math 20C Multivariable Calculus Lecture 3 Differentiable functions (Sec. 4.4) Review: Partial derivatives. Slide Partial derivatives and continuity. Equation of the tangent plane. Differentiable functions.

More information

Calculus II Fall 2014

Calculus II Fall 2014 Calculus II Fall 2014 Lecture 3 Partial Derivatives Eitan Angel University of Colorado Monday, December 1, 2014 E. Angel (CU) Calculus II 1 Dec 1 / 13 Introduction Much of the calculus of several variables

More information

Square Waves, Sinusoids and Gaussian White Noise: A Matching Pursuit Conundrum? Don Percival

Square Waves, Sinusoids and Gaussian White Noise: A Matching Pursuit Conundrum? Don Percival Square Waves, Sinusoids and Gaussian Whie Noise: A Maching Pursui Conundrum? Don Percival Applied Physics Laboraory Deparmen of Saisics Universiy of Washingon Seale, Washingon, USA hp://faculy.washingon.edu/dbp

More information

Exam 2 Review Sheet. r(t) = x(t), y(t), z(t)

Exam 2 Review Sheet. r(t) = x(t), y(t), z(t) Exam 2 Review Sheet Joseph Breen Particle Motion Recall that a parametric curve given by: r(t) = x(t), y(t), z(t) can be interpreted as the position of a particle. Then the derivative represents the particle

More information

Experiment 6: Transmission Line Pulse Response

Experiment 6: Transmission Line Pulse Response Eperimen 6: Transmission Line Pulse Response Lossless Disribued Neworks When he ime required for a pulse signal o raverse a circui is on he order of he rise or fall ime of he pulse, i is no longer possible

More information

Notes on the Fourier Transform

Notes on the Fourier Transform Noes on he Fourier Transform The Fourier ransform is a mahemaical mehod for describing a coninuous funcion as a series of sine and cosine funcions. The Fourier Transform is produced by applying a series

More information

Announcement. Allowed

Announcement. Allowed 9//05 nnouncemen Firs es: Sep. 8, Chap. -4 llowed wriing insrumen poce calculaor ruler One 8.5" " paper conaining consans, formulas, and any oher informaion ha you migh find useful (NOT any inds of soluions).

More information

5 Spatial Relations on Lines

5 Spatial Relations on Lines 5 Spaial Relaions on Lines There are number of useful problems ha can be solved wih he basic consrucion echniques developed hus far. We now look a cerain problems, which involve spaial relaionships beween

More information

Maxima and Minima. Terminology note: Do not confuse the maximum f(a, b) (a number) with the point (a, b) where the maximum occurs.

Maxima and Minima. Terminology note: Do not confuse the maximum f(a, b) (a number) with the point (a, b) where the maximum occurs. 10-11-2010 HW: 14.7: 1,5,7,13,29,33,39,51,55 Maxima and Minima In this very important chapter, we describe how to use the tools of calculus to locate the maxima and minima of a function of two variables.

More information

2.1 Partial Derivatives

2.1 Partial Derivatives .1 Partial Derivatives.1.1 Functions of several variables Up until now, we have only met functions of single variables. From now on we will meet functions such as z = f(x, y) and w = f(x, y, z), which

More information

Double Tangent Sampling Method for Sinusoidal Pulse Width Modulation

Double Tangent Sampling Method for Sinusoidal Pulse Width Modulation Compuaional and Applied Mahemaics Journal 2018; 4(1): 8-14 hp://www.aasci.org/journal/camj ISS: 2381-1218 (Prin); ISS: 2381-1226 (Online) Double Tangen Sampling Mehod for Sinusoidal Pulse Widh Modulaion

More information

Calculus of Several Variables

Calculus of Several Variables Benjamin McKay Calculus of Several Variables Optimisation and Finance February 18, 2018 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Preface The course is

More information

Chapter 2 Introduction: From Phase-Locked Loop to Costas Loop

Chapter 2 Introduction: From Phase-Locked Loop to Costas Loop Chaper 2 Inroducion: From Phase-Locked Loop o Cosas Loop The Cosas loop can be considered an exended version of he phase-locked loop (PLL). The PLL has been invened in 932 by French engineer Henri de Belleszice

More information

Table of Contents. 3.0 SMPS Topologies. For Further Research. 3.1 Basic Components. 3.2 Buck (Step Down) 3.3 Boost (Step Up) 3.4 Inverter (Buck/Boost)

Table of Contents. 3.0 SMPS Topologies. For Further Research. 3.1 Basic Components. 3.2 Buck (Step Down) 3.3 Boost (Step Up) 3.4 Inverter (Buck/Boost) Table of Conens 3.0 SMPS Topologies 3.1 Basic Componens 3.2 Buck (Sep Down) 3.3 Boos (Sep Up) 3.4 nverer (Buck/Boos) 3.5 Flyback Converer 3.6 Curren Boosed Boos 3.7 Curren Boosed Buck 3.8 Forward Converer

More information

MATLAB/SIMULINK TECHNOLOGY OF THE SYGNAL MODULATION

MATLAB/SIMULINK TECHNOLOGY OF THE SYGNAL MODULATION J Modern Technology & Engineering Vol2, No1, 217, pp76-81 MATLAB/SIMULINK TECHNOLOGY OF THE SYGNAL MODULATION GA Rusamov 1*, RJ Gasimov 1, VG Farhadov 1 1 Azerbaijan Technical Universiy, Baku, Azerbaijan

More information

Lecture 19 - Partial Derivatives and Extrema of Functions of Two Variables

Lecture 19 - Partial Derivatives and Extrema of Functions of Two Variables Lecture 19 - Partial Derivatives and Extrema of Functions of Two Variables 19.1 Partial Derivatives We wish to maximize functions of two variables. This will involve taking derivatives. Example: Consider

More information

Lines and Angles Notes Geometry Unit 3: Lesson 1. Parallel lines. Skew lines. Parallel planes. Transversal. Alternate Interior Angles t

Lines and Angles Notes Geometry Unit 3: Lesson 1. Parallel lines. Skew lines. Parallel planes. Transversal. Alternate Interior Angles t Lines and Angles Noes Geoery Uni 3: Lesson 1 Nae Parallel lines D C Skew lines A B Parallel planes E H F G Transversal Alernae Inerior Angles, 4 1 2 3 l Alernae Exerior Angles, 5 6 8 7 Corresponding Angles,,,

More information

Pointwise Image Operations

Pointwise Image Operations Poinwise Image Operaions Binary Image Analysis Jana Kosecka hp://cs.gmu.edu/~kosecka/cs482.hml - Lookup able mach image inensiy o he displayed brighness values Manipulaion of he lookup able differen Visual

More information

Chapter 2 Summary: Continuous-Wave Modulation. Belkacem Derras

Chapter 2 Summary: Continuous-Wave Modulation. Belkacem Derras ECEN 44 Communicaion Theory Chaper Summary: Coninuous-Wave Modulaion.1 Modulaion Modulaion is a process in which a parameer of a carrier waveform is varied in accordance wih a given message (baseband)

More information

Memorandum on Impulse Winding Tester

Memorandum on Impulse Winding Tester Memorandum on Impulse Winding Teser. Esimaion of Inducance by Impulse Response When he volage response is observed afer connecing an elecric charge sored up in he capaciy C o he coil L (including he inside

More information

Exam 2 Summary. 1. The domain of a function is the set of all possible inputes of the function and the range is the set of all outputs.

Exam 2 Summary. 1. The domain of a function is the set of all possible inputes of the function and the range is the set of all outputs. Exam 2 Summary Disclaimer: The exam 2 covers lectures 9-15, inclusive. This is mostly about limits, continuity and differentiation of functions of 2 and 3 variables, and some applications. The complete

More information

Lecture September 6, 2011

Lecture September 6, 2011 cs294-p29 Seminar on Algorihmic Game heory Sepember 6, 2011 Lecure Sepember 6, 2011 Lecurer: Chrisos H. Papadimiriou Scribes: Aloni Cohen and James Andrews 1 Game Represenaion 1.1 abular Form and he Problem

More information

Review Exercises for Chapter 10

Review Exercises for Chapter 10 60_00R.q //0 :8 M age 756 756 CHATER 0 Conics, arameric Equaions, an olar Coorinaes Review Eercises for Chaper 0 See www.calccha.com for worke-ou soluions o o-numbere eercises. In Eercises 6, mach he equaion

More information

Passband Data Transmission II References Frequency-shift keying Chapter 6.5, S. Haykin, Communication Systems, Wiley. H.1

Passband Data Transmission II References Frequency-shift keying Chapter 6.5, S. Haykin, Communication Systems, Wiley. H.1 Passand Daa ransmission II Reerences Frequency-shi keying Chaper 6.5, S. Haykin, Communicaion Sysems, Wiley. H. Inroducion Inroducion PSK and QAM are linear modulaion FSK is a nonlinear modulaion Similar

More information

Social-aware Dynamic Router Node Placement in Wireless Mesh Networks

Social-aware Dynamic Router Node Placement in Wireless Mesh Networks Social-aware Dynamic Rouer Node Placemen in Wireless Mesh Neworks Chun-Cheng Lin Pei-Tsung Tseng Ting-Yu Wu Der-Jiunn Deng ** Absrac The problem of dynamic rouer node placemen (dynrnp) in wireless mesh

More information

TELE4652 Mobile and Satellite Communications

TELE4652 Mobile and Satellite Communications TELE465 Mobile and Saellie Communicaions Assignmen (Due: 4pm, Monday 7 h Ocober) To be submied o he lecurer before he beginning of he final lecure o be held a his ime.. This quesion considers Minimum Shif

More information

ANALOG AND DIGITAL SIGNAL PROCESSING LABORATORY EXPERIMENTS : CHAPTER 3

ANALOG AND DIGITAL SIGNAL PROCESSING LABORATORY EXPERIMENTS : CHAPTER 3 Laboraory # Chap 3 Objecives Linear Sysem Response: general case Undersand he difference and he relaionship beween a sep and impulse response. Deermine he limis of validiy of an approximaed impulse response.

More information

Explanation of Maximum Ratings and Characteristics for Thyristors

Explanation of Maximum Ratings and Characteristics for Thyristors 8 Explanaion of Maximum Raings and Characerisics for Thyrisors Inroducion Daa shees for s and riacs give vial informaion regarding maximum raings and characerisics of hyrisors. If he maximum raings of

More information

Development and Validation of Flat-Plate Collector Testing Procedures

Development and Validation of Flat-Plate Collector Testing Procedures Developmen and Validaion of Fla-Plae Collecor Tesing Procedures Repor for November, 2006 Focus on Energy (FOE) suppors solar hermal sysems ha displace convenional fuels by offering cash-back rebaes ha

More information

Robot Control using Genetic Algorithms

Robot Control using Genetic Algorithms Robo Conrol using Geneic Algorihms Summary Inroducion Robo Conrol Khepera Simulaor Geneic Model for Pah Planning Chromosome Represenaion Evaluaion Funcion Case Sudies Conclusions The Robo Conroller Problem

More information

Independence of Path and Conservative Vector Fields

Independence of Path and Conservative Vector Fields Independence of Path and onservative Vector Fields MATH 311, alculus III J. Robert Buchanan Department of Mathematics Summer 2011 Goal We would like to know conditions on a vector field function F(x, y)

More information

Independent of path Green s Theorem Surface Integrals. MATH203 Calculus. Dr. Bandar Al-Mohsin. School of Mathematics, KSU 20/4/14

Independent of path Green s Theorem Surface Integrals. MATH203 Calculus. Dr. Bandar Al-Mohsin. School of Mathematics, KSU 20/4/14 School of Mathematics, KSU 20/4/14 Independent of path Theorem 1 If F (x, y) = M(x, y)i + N(x, y)j is continuous on an open connected region D, then the line integral F dr is independent of path if and

More information

Passband Data Transmission I References Phase-shift keying Chapter , S. Haykin, Communication Systems, Wiley. G.1

Passband Data Transmission I References Phase-shift keying Chapter , S. Haykin, Communication Systems, Wiley. G.1 Passand Daa ransmission I References Phase-shif keying Chaper 4.-4.3, S. Haykin, Communicaion Sysems, Wiley. G. Inroducion Inroducion In aseand pulse ransmission, a daa sream represened in he form of a

More information

ECMA-373. Near Field Communication Wired Interface (NFC-WI) 2 nd Edition / June Reference number ECMA-123:2009

ECMA-373. Near Field Communication Wired Interface (NFC-WI) 2 nd Edition / June Reference number ECMA-123:2009 ECMA-373 2 nd Ediion / June 2012 Near Field Communicaion Wired Inerface (NFC-WI) Reference number ECMA-123:2009 Ecma Inernaional 2009 COPYRIGHT PROTECTED DOCUMENT Ecma Inernaional 2012 Conens Page 1 Scope...

More information

READING ASSIGNMENTS LECTURE OBJECTIVES. Problem Solving Skills. x(t) = cos(αt 2 ) ELEG-212 Signal Processing and Communications

READING ASSIGNMENTS LECTURE OBJECTIVES. Problem Solving Skills. x(t) = cos(αt 2 ) ELEG-212 Signal Processing and Communications ELEG- Signal Processing and Communicaions Lecure 5 Periodic Signals, Harmonics & ime-varying Sinusoids READING ASSIGNMENS his Lecure: Chaper 3, Secions 3- and 3-3 Chaper 3, Secions 3-7 and 3-8 Lab sars

More information

ELEG 3124 SYSTEMS AND SIGNALS Ch. 1 Continuous-Time Signals

ELEG 3124 SYSTEMS AND SIGNALS Ch. 1 Continuous-Time Signals Deparmen of Elecrical Engineering Universiy of Arkansas ELEG 3124 SYSTEMS AND SIGNALS Ch. 1 Coninuous-Time Signals Dr. Jingxian Wu wuj@uark.edu OUTLINE 2 Inroducion: wha are signals and sysems? Signals

More information

Communications II Lecture 7: Performance of digital modulation

Communications II Lecture 7: Performance of digital modulation Communicaions II Lecure 7: Performance of digial modulaion Professor Kin K. Leung EEE and Compuing Deparmens Imperial College London Copyrigh reserved Ouline Digial modulaion and demodulaion Error probabiliy

More information

P. Bruschi: Project guidelines PSM Project guidelines.

P. Bruschi: Project guidelines PSM Project guidelines. Projec guidelines. 1. Rules for he execuion of he projecs Projecs are opional. Their aim is o improve he sudens knowledge of he basic full-cusom design flow. The final score of he exam is no affeced by

More information

AN303 APPLICATION NOTE

AN303 APPLICATION NOTE AN303 APPLICATION NOTE LATCHING CURRENT INTRODUCTION An imporan problem concerning he uilizaion of componens such as hyrisors or riacs is he holding of he componen in he conducing sae afer he rigger curren

More information

Math Final Exam - 6/11/2015

Math Final Exam - 6/11/2015 Math 200 - Final Exam - 6/11/2015 Name: Section: Section Class/Times Instructor Section Class/Times Instructor 1 9:00%AM ( 9:50%AM Papadopoulos,%Dimitrios 11 1:00%PM ( 1:50%PM Swartz,%Kenneth 2 11:00%AM

More information

Estimating a Time-Varying Phillips Curve for South Africa

Estimating a Time-Varying Phillips Curve for South Africa Esimaing a Time-Varying Phillips Curve for Souh Africa Alain Kabundi* 1 Eric Schaling** Modese Some*** *Souh African Reserve Bank ** Wis Business School and VU Universiy Amserdam *** World Bank 27 Ocober

More information

Principles of Communications

Principles of Communications Sae Key Lab. on ISN, Xidian Universiy Principles of Communicaions Chaper VI: Elemenary Digial Modulaion Sysem Email: ychwang@mail.xidian.edu.cn Xidian Universiy Sae Key Lab. on ISN December 13, 2013 Sae

More information

ANSWER KEY. (a) For each of the following partials derivatives, use the contour plot to decide whether they are positive, negative, or zero.

ANSWER KEY. (a) For each of the following partials derivatives, use the contour plot to decide whether they are positive, negative, or zero. Math 2130-101 Test #2 for Section 101 October 14 th, 2009 ANSWE KEY 1. (10 points) Compute the curvature of r(t) = (t + 2, 3t + 4, 5t + 6). r (t) = (1, 3, 5) r (t) = 1 2 + 3 2 + 5 2 = 35 T(t) = 1 r (t)

More information

Signal processing for Underwater Acoustic MIMO OFDM

Signal processing for Underwater Acoustic MIMO OFDM Signal processing for Underwaer Acousic MIMO OFDM Milica Sojanovic Norheasern Universiy millisa@ece.neu.edu ONR (N4-7--22, 7 22 MURI N4-7--738) 7 738) Orhogonal frequency division muliplexing (OFDM) oal

More information

Free and Forced Vibrations of Two Degree of Systems

Free and Forced Vibrations of Two Degree of Systems ree and orced Vibraions of Two Degree of Syses Inroducion: The siple single degree-of-freedo syse can be coupled o anoher of is ind, producing a echanical syse described by wo coupled differenial equaions;

More information

Evaluation of Instantaneous Reliability Measures for a Gradual Deteriorating System

Evaluation of Instantaneous Reliability Measures for a Gradual Deteriorating System General Leers in Mahemaic, Vol. 3, No.3, Dec 27, pp. 77-85 e-issn 259-9277, p-issn 259-9269 Available online a hp:\\ www.refaad.com Evaluaion of Insananeous Reliabiliy Measures for a Gradual Deerioraing

More information

Modulation exercises. Chapter 3

Modulation exercises. Chapter 3 Chaper 3 Modulaion exercises Each problem is annoaed wih he leer E, T, C which sands for exercise, requires some hough, requires some concepualizaion. Problems labeled E are usually mechanical, hose labeled

More information

(This lesson plan assumes the students are using an air-powered rocket as described in the Materials section.)

(This lesson plan assumes the students are using an air-powered rocket as described in the Materials section.) The Mah Projecs Journal Page 1 PROJECT MISSION o MArs inroducion Many sae mah sandards and mos curricula involving quadraic equaions require sudens o solve "falling objec" or "projecile" problems, which

More information

Chapter 16. Partial Derivatives

Chapter 16. Partial Derivatives Chapter 16 Partial Derivatives The use of contour lines to help understand a function whose domain is part of the plane goes back to the year 1774. A group of surveyors had collected a large number of

More information

Dead Zone Compensation Method of H-Bridge Inverter Series Structure

Dead Zone Compensation Method of H-Bridge Inverter Series Structure nd Inernaional Conference on Elecrical, Auomaion and Mechanical Engineering (EAME 7) Dead Zone Compensaion Mehod of H-Bridge Inverer Series Srucure Wei Li Insiue of Elecrical Engineering and Informaion

More information

Signals and the frequency domain ENGR 40M lecture notes July 31, 2017 Chuan-Zheng Lee, Stanford University

Signals and the frequency domain ENGR 40M lecture notes July 31, 2017 Chuan-Zheng Lee, Stanford University Signals and he requency domain ENGR 40M lecure noes July 3, 07 Chuan-Zheng Lee, Sanord Universiy signal is a uncion, in he mahemaical sense, normally a uncion o ime. We oen reer o uncions as signals o

More information

Math 148 Exam III Practice Problems

Math 148 Exam III Practice Problems Math 48 Exam III Practice Problems This review should not be used as your sole source for preparation for the exam. You should also re-work all examples given in lecture, all homework problems, all lab

More information

(d) If a particle moves at a constant speed, then its velocity and acceleration are perpendicular.

(d) If a particle moves at a constant speed, then its velocity and acceleration are perpendicular. Math 142 -Review Problems II (Sec. 10.2-11.6) Work on concept check on pages 734 and 822. More review problems are on pages 734-735 and 823-825. 2nd In-Class Exam, Wednesday, April 20. 1. True - False

More information

The Chain Rule, Higher Partial Derivatives & Opti- mization

The Chain Rule, Higher Partial Derivatives & Opti- mization The Chain Rule, Higher Partial Derivatives & Opti- Unit #21 : mization Goals: We will study the chain rule for functions of several variables. We will compute and study the meaning of higher partial derivatives.

More information

ECMA st Edition / June Near Field Communication Wired Interface (NFC-WI)

ECMA st Edition / June Near Field Communication Wired Interface (NFC-WI) ECMA-373 1 s Ediion / June 2006 Near Field Communicaion Wired Inerface (NFC-WI) Sandard ECMA-373 1 s Ediion / June 2006 Near Field Communicaion Wired Inerface (NFC-WI) Ecma Inernaional Rue du Rhône 114

More information

Analog Circuits EC / EE / IN. For

Analog Circuits EC / EE / IN.   For Analog Circuis For EC / EE / IN By www.hegaeacademy.com Syllabus Syllabus for Analog Circuis Small Signal Equivalen Circuis of Diodes, BJTs, MOSFETs and Analog CMOS. Simple Diode Circuis, Clipping, Clamping,

More information

Math for Economics 1 New York University FINAL EXAM, Fall 2013 VERSION A

Math for Economics 1 New York University FINAL EXAM, Fall 2013 VERSION A Math for Economics 1 New York University FINAL EXAM, Fall 2013 VERSION A Name: ID: Circle your instructor and lecture below: Jankowski-001 Jankowski-006 Ramakrishnan-013 Read all of the following information

More information

Variation Aware Cross-Talk Aggressor Alignment by Mixed Integer Linear Programming

Variation Aware Cross-Talk Aggressor Alignment by Mixed Integer Linear Programming ariaion Aware Cross-alk Aggressor Alignmen by Mixed Ineger Linear Programming ladimir Zoloov IBM. J. Wason Research Cener, Yorkown Heighs, NY zoloov@us.ibm.com Peer Feldmann D. E. Shaw Research, New York,

More information

Errata and Updates for ASM Exam MLC (Fourteenth Edition) Sorted by Page

Errata and Updates for ASM Exam MLC (Fourteenth Edition) Sorted by Page Erraa for ASM Exam MLC Sudy Manual (Foureenh Ediion) Sored by Page 1 Erraa and Updaes for ASM Exam MLC (Foureenh Ediion) Sored by Page Pracice Exam 7:25 (page 1386) is defecive, Pracice Exam 5:21 (page

More information

B) 0 C) 1 D) No limit. x2 + y2 4) A) 2 B) 0 C) 1 D) No limit. A) 1 B) 2 C) 0 D) No limit. 8xy 6) A) 1 B) 0 C) π D) -1

B) 0 C) 1 D) No limit. x2 + y2 4) A) 2 B) 0 C) 1 D) No limit. A) 1 B) 2 C) 0 D) No limit. 8xy 6) A) 1 B) 0 C) π D) -1 MTH 22 Exam Two - Review Problem Set Name Sketch the surface z = f(x,y). ) f(x, y) = - x2 ) 2) f(x, y) = 2 -x2 - y2 2) Find the indicated limit or state that it does not exist. 4x2 + 8xy + 4y2 ) lim (x,

More information

unmodulated carrier phase refference /2 /2 3π/2 APSK /2 3/2 DPSK t/t s

unmodulated carrier phase refference /2 /2 3π/2 APSK /2 3/2 DPSK t/t s The PSK Modulaion - PSK is a modulaion ha modifies he phase of a carrier signal, a he beginning of he symbol period, wih a value ha depends on he mulibi ha has o be modulaed - i exhibis a good resilience

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se #8 C-T Sysems: Frequency-Domain Analysis of Sysems Reading Assignmen: Secion 5.2 of Kamen and Heck /2 Course Flow Diagram The arrows here show concepual

More information