zt ( ) = Ae find f(t)=re( zt ( )), g(t)= Im( zt ( )), and r(t), and θ ( t) if z(t)=r(t) e

Size: px
Start display at page:

Download "zt ( ) = Ae find f(t)=re( zt ( )), g(t)= Im( zt ( )), and r(t), and θ ( t) if z(t)=r(t) e"

Transcription

1 Homework # Fundamentals Review Homework or EECS 562 (As needed or plotting you can use Matlab or another sotware tool or your choice) π. Plot x ( t) = 2cos(2π5 t), x ( t) = 2cos(2π5( t.25)), and x ( t) = 2cos(2π5 t ) 2 Compare these three signals and explain their similarities and dierences. 2. Let j z = + j ind: Re( z ), Im( z ), z and z and α and β i z = αe β 2. Let z(t) be a complex signal c + zt ( ) = Ae ind (t)=re( zt ( )), g(t)= Im( zt ( )), and r(t), and θ ( t) i z(t)=r(t) e j(2 π t φ) jθ () t. Let z = + j, z = j, z = + j, z = j 2 j2π t c Re( ze i ) or i =... Find 5. Find cos(2 π t)sin(2 π t) dt and what property describes the relationship between cos(2 πt) and sin(2 πt )? 6. For x( t) = 2cos( πt) sin(2 πt ) a) What is the undamental requency? b) Find the complex Fourier series or x(t). [Hint: no integration is required or this problem, convert cos( πt) and sin(2 πt ) into their complex exponential orms and note sin(α)=cos(α-π/2) and cos(α)=cos(α π)] c) Plot the double sided phase and amplitude spectrum or x(t). d) What is the power in x(t)? e) What is the bandwidth o x(t)? 7. A bit is transmitted as x(t) = cos(2πt) or a or cos(2πt) or a or ms. Find the energy and power in x(t). Ex= Px=

2 8. An input signal x(t) is processed by a ilter with an amplitude H() and phase θ() response given below. a) For x ( t) = 2cos(2π 5 t) ind output signal ya(t). a b) For x ( t) = cos(2π 75 t) ind output signal yb(t). b c) For x ( t) = 2cos(2π5 t) + cos(2π75 t) ind output signal yc(t). c d) For x ( t) = cos(2π 5 t) ind output signal yd(t). d e) For x ( t) = 2cos(2π5 t) + cos(2π5 t) ind output signal ye(t). e ) For x ( t) = 2cos(2π5 t) + cos(2π5 t) ind output signal y(t). g) Which input signal above, xa(t) x(t) has the largest bandwidth and what is that bandwidth? h) An input signal x(t) with a bandwidth B is processed by a ilter with an amplitude H() and phase θ() response given above. What is the maximum value o B that will result in distortion-less transmission o an input signal x(t) through the ilter, H()? 9. A linear time-invariant system with input signal x(t) produces an output signal y(t) =α x(t-τ), ind the system transer unction and impulse response.. The spectrum o x(t) is given below: a) The signal x(t) is sampled at 7 samples/sec to orm xs(t). Plot the spectrum o xs(t). b) For x(t) given above, what is the minimum sample rate required to prevent aliasing? c) I no aliasing is present, describe how x(t) is recovered rom xs(t). 2

3 . Two linear time invariant systems have transer unctions o H and H2 are conigured as: z(t) x(t) H() H2() y(t) x(t) H() y(t) System System 2 H and H2 have the ollowing transer unctions H ( ) = e H ( ) = + j2π j2 π (.) 2 a) Find H() such that the two systems above (System and System 2) are the same, i.e., or the same input x(t) ind H() such that System and System 2 produce the same output. b) Plot H2() c) Find h2(t). d) Find the output signal, y(t), when the input signal is x( t) = cos(2 πt). e) Is the system H() casual, Circle YES or NO, Justiy your answer. 2. An ideal bandpass ilter H() has center requency o 2 khz and bandwidth Bh= khz. The input to H() is x(t), where t kt x ( t ) = rect τ = µ = µ = τ where s and T 5 s k a) Plot H(), label axis. b) Plot X(), label axis. c) Find the power in x(t) at the undamental requency. d) For the x(t) and H() given above ind the system output y(t). [Hint: Examine the results o part a) and b) and note Y()=X()H()]

4 . Consider a linear time invariant system with a impulse response o h(t), and input signal x(t) given below. The input signal x(t) given below produces and output o y(t). x(t) exp(-t) - time h(t) time a) What is y(-5)? b) What is y(-.5)? c) What is y(.5)?. The signal x[n] is input to a LTI system with impulse response h[n]. x[n] 2 n h[n] 5 n Find the discrete time convolution o x[n]*h[n]=y[n].

5 5. A radar signal has a bandwidth o about 5 MHz. A DFT is use to analyze the requency content o a radar signal with a requency resolution o khz. a) To achieve this requency resolution what is the required record length in seconds? b) How many samples are in the record, state any assumptions? 6. Properties o the DFT. (For this problem use Matlab or another sotware tool or your choice) a) Let X[n] = cos(nπ/2), n=...6. Plot the magnitude o the DFT o X[n]. b) Let X2[n]=, n=.., cos(nπ/2), n=5..6. Plot the magnitude o the DFT o X2[n]. Explain the dierence between the results o part a) and part b). 7. Let s(t)= x(t)sin(2π o t) where o= MHz and X ( ) = rect ( ) 2 a) Plot the amplitude spectrum o s(t). b) Find the output y(t) o the ollowing system in terms o x(t). The bandwidth o the ILPF 2 is khz. [Hints: sin ( θ) = cos(2 θ) and then plot the spectrum o the signal at the 2 2 input to the ILPF] 5

( ) D. An information signal x( t) = 5cos( 1000πt) LSSB modulates a carrier with amplitude A c

( ) D. An information signal x( t) = 5cos( 1000πt) LSSB modulates a carrier with amplitude A c An inormation signal x( t) 5cos( 1000πt) LSSB modulates a carrier with amplitude A c 1. This signal is transmitted through a channel with 30 db loss. It is demodulated using a synchronous demodulator.

More information

The University of Texas at Austin Dept. of Electrical and Computer Engineering Midterm #2

The University of Texas at Austin Dept. of Electrical and Computer Engineering Midterm #2 The University of Texas at Austin Dept. of Electrical and Computer Engineering Midterm #2 Date: November 18, 2010 Course: EE 313 Evans Name: Last, First The exam is scheduled to last 75 minutes. Open books

More information

Experiments #6. Convolution and Linear Time Invariant Systems

Experiments #6. Convolution and Linear Time Invariant Systems Experiments #6 Convolution and Linear Time Invariant Systems 1) Introduction: In this lab we will explain how to use computer programs to perform a convolution operation on continuous time systems and

More information

Project I: Phase Tracking and Baud Timing Correction Systems

Project I: Phase Tracking and Baud Timing Correction Systems Project I: Phase Tracking and Baud Timing Correction Systems ECES 631, Prof. John MacLaren Walsh, Ph. D. 1 Purpose In this lab you will encounter the utility of the fundamental Fourier and z-transform

More information

Midterm 1. Total. Name of Student on Your Left: Name of Student on Your Right: EE 20N: Structure and Interpretation of Signals and Systems

Midterm 1. Total. Name of Student on Your Left: Name of Student on Your Right: EE 20N: Structure and Interpretation of Signals and Systems EE 20N: Structure and Interpretation of Signals and Systems Midterm 1 12:40-2:00, February 19 Notes: There are five questions on this midterm. Answer each question part in the space below it, using the

More information

Lecture 2 Review of Signals and Systems: Part 1. EE4900/EE6720 Digital Communications

Lecture 2 Review of Signals and Systems: Part 1. EE4900/EE6720 Digital Communications EE4900/EE6420: Digital Communications 1 Lecture 2 Review of Signals and Systems: Part 1 Block Diagrams of Communication System Digital Communication System 2 Informatio n (sound, video, text, data, ) Transducer

More information

Final Exam Solutions June 7, 2004

Final Exam Solutions June 7, 2004 Name: Final Exam Solutions June 7, 24 ECE 223: Signals & Systems II Dr. McNames Write your name above. Keep your exam flat during the entire exam period. If you have to leave the exam temporarily, close

More information

Final Exam Solutions June 14, 2006

Final Exam Solutions June 14, 2006 Name or 6-Digit Code: PSU Student ID Number: Final Exam Solutions June 14, 2006 ECE 223: Signals & Systems II Dr. McNames Keep your exam flat during the entire exam. If you have to leave the exam temporarily,

More information

Signals and Systems Lecture 6: Fourier Applications

Signals and Systems Lecture 6: Fourier Applications Signals and Systems Lecture 6: Fourier Applications Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Winter 2012 arzaneh Abdollahi Signal and Systems Lecture 6

More information

2.1 BASIC CONCEPTS Basic Operations on Signals Time Shifting. Figure 2.2 Time shifting of a signal. Time Reversal.

2.1 BASIC CONCEPTS Basic Operations on Signals Time Shifting. Figure 2.2 Time shifting of a signal. Time Reversal. 1 2.1 BASIC CONCEPTS 2.1.1 Basic Operations on Signals Time Shifting. Figure 2.2 Time shifting of a signal. Time Reversal. 2 Time Scaling. Figure 2.4 Time scaling of a signal. 2.1.2 Classification of Signals

More information

EELE503. Modern filter design. Filter Design - Introduction

EELE503. Modern filter design. Filter Design - Introduction EELE503 Modern filter design Filter Design - Introduction A filter will modify the magnitude or phase of a signal to produce a desired frequency response or time response. One way to classify ideal filters

More information

HW 6 Due: November 3, 10:39 AM (in class)

HW 6 Due: November 3, 10:39 AM (in class) ECS 332: Principles of Communications 2015/1 HW 6 Due: November 3, 10:39 AM (in class) Lecturer: Prapun Suksompong, Ph.D. Instructions (a) ONE part of a question will be graded (5 pt). Of course, you do

More information

1. Clearly circle one answer for each part.

1. Clearly circle one answer for each part. TB 1-9 / Exam Style Questions 1 EXAM STYLE QUESTIONS Covering Chapters 1-9 of Telecommunication Breakdown 1. Clearly circle one answer for each part. (a) TRUE or FALSE: Absolute bandwidth is never less

More information

Project 2 - Speech Detection with FIR Filters

Project 2 - Speech Detection with FIR Filters Project 2 - Speech Detection with FIR Filters ECE505, Fall 2015 EECS, University of Tennessee (Due 10/30) 1 Objective The project introduces a practical application where sinusoidal signals are used to

More information

Traditional Analog Modulation Techniques

Traditional Analog Modulation Techniques Chapter 5 Traditional Analog Modulation Techniques Mikael Olosson 2002 2007 Modulation techniques are mainly used to transmit inormation in a given requency band. The reason or that may be that the channel

More information

EITG05 Digital Communications

EITG05 Digital Communications Fourier transform EITG05 Digital Communications Lecture 4 Bandwidth of Transmitted Signals Michael Lentmaier Thursday, September 3, 08 X(f )F{x(t)} x(t) e jπ ft dt X Re (f )+jx Im (f ) X(f ) e jϕ(f ) x(t)f

More information

Problems from the 3 rd edition

Problems from the 3 rd edition (2.1-1) Find the energies of the signals: a) sin t, 0 t π b) sin t, 0 t π c) 2 sin t, 0 t π d) sin (t-2π), 2π t 4π Problems from the 3 rd edition Comment on the effect on energy of sign change, time shifting

More information

Sinusoidal signal. Arbitrary signal. Periodic rectangular pulse. Sampling function. Sampled sinusoidal signal. Sampled arbitrary signal

Sinusoidal signal. Arbitrary signal. Periodic rectangular pulse. Sampling function. Sampled sinusoidal signal. Sampled arbitrary signal Techniques o Physics Worksheet 4 Digital Signal Processing 1 Introduction to Digital Signal Processing The ield o digital signal processing (DSP) is concerned with the processing o signals that have been

More information

A MATLAB Model of Hybrid Active Filter Based on SVPWM Technique

A MATLAB Model of Hybrid Active Filter Based on SVPWM Technique International Journal o Electrical Engineering. ISSN 0974-2158 olume 5, Number 5 (2012), pp. 557-569 International Research Publication House http://www.irphouse.com A MATLAB Model o Hybrid Active Filter

More information

Solution to Chapter 4 Problems

Solution to Chapter 4 Problems Solution to Chapter 4 Problems Problem 4.1 1) Since F[sinc(400t)]= 1 modulation index 400 ( f 400 β f = k f max[ m(t) ] W Hence, the modulated signal is ), the bandwidth of the message signal is W = 00

More information

The University of Texas at Austin Dept. of Electrical and Computer Engineering Final Exam

The University of Texas at Austin Dept. of Electrical and Computer Engineering Final Exam The University of Texas at Austin Dept. of Electrical and Computer Engineering Final Exam Date: December 18, 2017 Course: EE 313 Evans Name: Last, First The exam is scheduled to last three hours. Open

More information

Final Exam. EE313 Signals and Systems. Fall 1999, Prof. Brian L. Evans, Unique No

Final Exam. EE313 Signals and Systems. Fall 1999, Prof. Brian L. Evans, Unique No Final Exam EE313 Signals and Systems Fall 1999, Prof. Brian L. Evans, Unique No. 14510 December 11, 1999 The exam is scheduled to last 50 minutes. Open books and open notes. You may refer to your homework

More information

Experiment 8: Sampling

Experiment 8: Sampling Prepared By: 1 Experiment 8: Sampling Objective The objective of this Lab is to understand concepts and observe the effects of periodically sampling a continuous signal at different sampling rates, changing

More information

1. In the command window, type "help conv" and press [enter]. Read the information displayed.

1. In the command window, type help conv and press [enter]. Read the information displayed. ECE 317 Experiment 0 The purpose of this experiment is to understand how to represent signals in MATLAB, perform the convolution of signals, and study some simple LTI systems. Please answer all questions

More information

Signals and Systems Lecture 6: Fourier Applications

Signals and Systems Lecture 6: Fourier Applications Signals and Systems Lecture 6: Fourier Applications Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Winter 2012 arzaneh Abdollahi Signal and Systems Lecture 6

More information

II. Random Processes Review

II. Random Processes Review II. Random Processes Review - [p. 2] RP Definition - [p. 3] RP stationarity characteristics - [p. 7] Correlation & cross-correlation - [p. 9] Covariance and cross-covariance - [p. 10] WSS property - [p.

More information

Introduction to OFDM. Characteristics of OFDM (Orthogonal Frequency Division Multiplexing)

Introduction to OFDM. Characteristics of OFDM (Orthogonal Frequency Division Multiplexing) Introduction to OFDM Characteristics o OFDM (Orthogonal Frequency Division Multiplexing Parallel data transmission with very long symbol duration - Robust under multi-path channels Transormation o a requency-selective

More information

DSP First. Laboratory Exercise #7. Everyday Sinusoidal Signals

DSP First. Laboratory Exercise #7. Everyday Sinusoidal Signals DSP First Laboratory Exercise #7 Everyday Sinusoidal Signals This lab introduces two practical applications where sinusoidal signals are used to transmit information: a touch-tone dialer and amplitude

More information

University of Toronto Electrical & Computer Engineering ECE 316, Winter 2015 Thursday, February 12, Test #1

University of Toronto Electrical & Computer Engineering ECE 316, Winter 2015 Thursday, February 12, Test #1 Name: Student No.: University of Toronto Electrical & Computer Engineering ECE 36, Winter 205 Thursday, February 2, 205 Test # Professor Dimitrios Hatzinakos Professor Deepa Kundur Duration: 50 minutes

More information

ECE5984 Orthogonal Frequency Division Multiplexing and Related Technologies Fall Mohamed Essam Khedr. Channel Estimation

ECE5984 Orthogonal Frequency Division Multiplexing and Related Technologies Fall Mohamed Essam Khedr. Channel Estimation ECE5984 Orthogonal Frequency Division Multiplexing and Related Technologies Fall 2007 Mohamed Essam Khedr Channel Estimation Matlab Assignment # Thursday 4 October 2007 Develop an OFDM system with the

More information

Communication Channels

Communication Channels Communication Channels wires (PCB trace or conductor on IC) optical fiber (attenuation 4dB/km) broadcast TV (50 kw transmit) voice telephone line (under -9 dbm or 110 µw) walkie-talkie: 500 mw, 467 MHz

More information

ECE 301, final exam of the session of Prof. Chih-Chun Wang Saturday 10:20am 12:20pm, December 20, 2008, STEW 130,

ECE 301, final exam of the session of Prof. Chih-Chun Wang Saturday 10:20am 12:20pm, December 20, 2008, STEW 130, ECE 301, final exam of the session of Prof. Chih-Chun Wang Saturday 10:20am 12:20pm, December 20, 2008, STEW 130, 1. Enter your name, student ID number, e-mail address, and signature in the space provided

More information

Instantaneous frequency Up to now, we have defined the frequency as the speed of rotation of a phasor (constant frequency phasor) φ( t) = A exp

Instantaneous frequency Up to now, we have defined the frequency as the speed of rotation of a phasor (constant frequency phasor) φ( t) = A exp Exponential modulation Instantaneous requency Up to now, we have deined the requency as the speed o rotation o a phasor (constant requency phasor) φ( t) = A exp j( ω t + θ ). We are going to generalize

More information

DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters

DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters Islamic University of Gaza OBJECTIVES: Faculty of Engineering Electrical Engineering Department Spring-2011 DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters To demonstrate the concept

More information

Basic Signals and Systems

Basic Signals and Systems Chapter 2 Basic Signals and Systems A large part of this chapter is taken from: C.S. Burrus, J.H. McClellan, A.V. Oppenheim, T.W. Parks, R.W. Schafer, and H. W. Schüssler: Computer-based exercises for

More information

Digital Signal Processing

Digital Signal Processing Digital Signal Processing Lecture 9 Discrete-Time Processing of Continuous-Time Signals Alp Ertürk alp.erturk@kocaeli.edu.tr Analog to Digital Conversion Most real life signals are analog signals These

More information

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises Digital Video and Audio Processing Winter term 2002/ 2003 Computer-based exercises Rudolf Mester Institut für Angewandte Physik Johann Wolfgang Goethe-Universität Frankfurt am Main 6th November 2002 Chapter

More information

Signals and Systems EE235. Leo Lam

Signals and Systems EE235. Leo Lam Signals and Systems EE235 Leo Lam Today s menu Lab detailed arrangements Homework vacation week From yesterday (Intro: Signals) Intro: Systems More: Describing Common Signals Taking a signal apart Offset

More information

ECE 201: Introduction to Signal Analysis

ECE 201: Introduction to Signal Analysis ECE 201: Introduction to Signal Analysis Prof. Paris Last updated: October 9, 2007 Part I Spectrum Representation of Signals Lecture: Sums of Sinusoids (of different frequency) Introduction Sum of Sinusoidal

More information

A Physical Sine-to-Square Converter Noise Model

A Physical Sine-to-Square Converter Noise Model A Physical Sine-to-Square Converter Noise Model Attila Kinali Max Planck Institute or Inormatics, Saarland Inormatics Campus, Germany adogan@mpi-in.mpg.de Abstract While sinusoid signal sources are used

More information

Sinusoids. Lecture #2 Chapter 2. BME 310 Biomedical Computing - J.Schesser

Sinusoids. Lecture #2 Chapter 2. BME 310 Biomedical Computing - J.Schesser Sinusoids Lecture # Chapter BME 30 Biomedical Computing - 8 What Is this Course All About? To Gain an Appreciation of the Various Types of Signals and Systems To Analyze The Various Types of Systems To

More information

HW 6 Due: November 9, 4 PM

HW 6 Due: November 9, 4 PM Name ID3 ECS 332: Principles of Communications 2018/1 HW 6 Due: November 9, 4 PM Lecturer: Prapun Suksompong, Ph.D. Instructions (a) This assignment has 10 pages. (b) (1 pt) Work and write your answers

More information

Lecture 10. Digital Modulation

Lecture 10. Digital Modulation Digital Modulation Lecture 10 On-Off keying (OOK), or amplitude shift keying (ASK) Phase shift keying (PSK), particularly binary PSK (BPSK) Frequency shift keying Typical spectra Modulation/demodulation

More information

Spread spectrum. Outline : 1. Baseband 2. DS/BPSK Modulation 3. CDM(A) system 4. Multi-path 5. Exercices. Exercise session 7 : Spread spectrum 1

Spread spectrum. Outline : 1. Baseband 2. DS/BPSK Modulation 3. CDM(A) system 4. Multi-path 5. Exercices. Exercise session 7 : Spread spectrum 1 Spread spectrum Outline : 1. Baseband 2. DS/BPSK Modulation 3. CDM(A) system 4. Multi-path 5. Exercices Exercise session 7 : Spread spectrum 1 1. Baseband +1 b(t) b(t) -1 T b t Spreading +1-1 T c t m(t)

More information

Digital communication

Digital communication Chapter 4 Digital communication A digital is a discrete-time binary m : Integers Bin = {0, 1}. To transmit such a it must first be transformed into a analog. The is then transmitted as such or modulated

More information

Handout 13: Intersymbol Interference

Handout 13: Intersymbol Interference ENGG 2310-B: Principles of Communication Systems 2018 19 First Term Handout 13: Intersymbol Interference Instructor: Wing-Kin Ma November 19, 2018 Suggested Reading: Chapter 8 of Simon Haykin and Michael

More information

Other Modulation Techniques - CAP, QAM, DMT

Other Modulation Techniques - CAP, QAM, DMT Other Modulation Techniques - CAP, QAM, DMT Prof. David Johns (johns@eecg.toronto.edu) (www.eecg.toronto.edu/~johns) slide 1 of 47 Complex Signals Concept useful for describing a pair of real signals Let

More information

3.6 Intersymbol interference. 1 Your site here

3.6 Intersymbol interference. 1 Your site here 3.6 Intersymbol intererence 1 3.6 Intersymbol intererence what is intersymbol intererence and what cause ISI 1. The absolute bandwidth o rectangular multilevel pulses is ininite. The channels bandwidth

More information

Problem Sheets: Communication Systems

Problem Sheets: Communication Systems Problem Sheets: Communication Systems Professor A. Manikas Chair of Communications and Array Processing Department of Electrical & Electronic Engineering Imperial College London v.11 1 Topic: Introductory

More information

EECS 452 Practice Midterm Exam Solutions Fall 2014

EECS 452 Practice Midterm Exam Solutions Fall 2014 EECS 452 Practice Midterm Exam Solutions Fall 2014 Name: unique name: Sign the honor code: I have neither given nor received aid on this exam nor observed anyone else doing so. Scores: # Points Section

More information

EEE - 321: Signals and Systems Lab Assignment 3

EEE - 321: Signals and Systems Lab Assignment 3 BILKENT UNIVERSITY ELECTRICAL AND ELECTRONICS ENGINEERING DEPARTMENT EEE - 321: Signals and Systems Lab Assignment 3 For Section-I report submission is due by 08.11.2017 For Section-II report submission

More information

Objectives. Presentation Outline. Digital Modulation Lecture 03

Objectives. Presentation Outline. Digital Modulation Lecture 03 Digital Modulation Lecture 03 Inter-Symbol Interference Power Spectral Density Richard Harris Objectives To be able to discuss Inter-Symbol Interference (ISI), its causes and possible remedies. To be able

More information

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 Purdue University: ECE438 - Digital Signal Processing with Applications 1 ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 1 Introduction

More information

Chapter-2 SAMPLING PROCESS

Chapter-2 SAMPLING PROCESS Chapter-2 SAMPLING PROCESS SAMPLING: A message signal may originate from a digital or analog source. If the message signal is analog in nature, then it has to be converted into digital form before it can

More information

ELE 635 Communication Systems. Assignment Problems and Solutions

ELE 635 Communication Systems. Assignment Problems and Solutions ELE 635 Communication Systems Assignment Problems and Solutions Winter 2015 CONTENTS Assignment 1: Signals and Signal Space 1.1 Problems... 1 1.2 Solutions... 3 Assignment 2: Analysis and Transmission

More information

Laboratory Assignment 5 Amplitude Modulation

Laboratory Assignment 5 Amplitude Modulation Laboratory Assignment 5 Amplitude Modulation PURPOSE In this assignment, you will explore the use of digital computers for the analysis, design, synthesis, and simulation of an amplitude modulation (AM)

More information

EEE 311: Digital Signal Processing I

EEE 311: Digital Signal Processing I EEE 311: Digital Signal Processing I Course Teacher: Dr Newaz Md Syur Rahim Associated Proessor, Dept o EEE, BUET, Dhaka 1000 Syllabus: As mentioned in your course calendar Reerence Books: 1 Digital Signal

More information

EEM 306 Introduction to Communications

EEM 306 Introduction to Communications EEM 306 Introduction to Communications Lecture 5 Department o Electrical and Electronics Engineering Anadolu University April 8, 2014 Lecture 5 1/20 Last Time Bandpass Systems Phase and Group Delay Introduction

More information

EE 311 February 13 and 15, 2019 Lecture 10

EE 311 February 13 and 15, 2019 Lecture 10 EE 311 February 13 and 15, 219 Lecture 1 Figure 4.22 The top figure shows a quantized sinusoid as the darker stair stepped curve. The bottom figure shows the quantization error. The quantized signal to

More information

Electrical & Computer Engineering Technology

Electrical & Computer Engineering Technology Electrical & Computer Engineering Technology EET 419C Digital Signal Processing Laboratory Experiments by Masood Ejaz Experiment # 1 Quantization of Analog Signals and Calculation of Quantized noise Objective:

More information

Lecture 7/8: UWB Channel. Kommunikations

Lecture 7/8: UWB Channel. Kommunikations Lecture 7/8: UWB Channel Kommunikations Technik UWB Propagation Channel Radio Propagation Channel Model is important for Link level simulation (bit error ratios, block error ratios) Coverage evaluation

More information

DSP First Lab 08: Frequency Response: Bandpass and Nulling Filters

DSP First Lab 08: Frequency Response: Bandpass and Nulling Filters DSP First Lab 08: Frequency Response: Bandpass and Nulling Filters Pre-Lab and Warm-Up: You should read at least the Pre-Lab and Warm-up sections of this lab assignment and go over all exercises in the

More information

EE456 Digital Communications

EE456 Digital Communications EE456 Digital Communications Professor Ha Nguyen September 216 EE456 Digital Communications 1 Angle Modulation In AM signals the information content of message m(t) is embedded as amplitude variation of

More information

Module 3 : Sampling and Reconstruction Problem Set 3

Module 3 : Sampling and Reconstruction Problem Set 3 Module 3 : Sampling and Reconstruction Problem Set 3 Problem 1 Shown in figure below is a system in which the sampling signal is an impulse train with alternating sign. The sampling signal p(t), the Fourier

More information

ECE 5655/4655 Laboratory Problems

ECE 5655/4655 Laboratory Problems Assignment #4 ECE 5655/4655 Laboratory Problems Make Note o the Following: Due Monday April 15, 2019 I possible write your lab report in Jupyter notebook I you choose to use the spectrum/network analyzer

More information

Wireless PHY: Modulation and Demodulation

Wireless PHY: Modulation and Demodulation Wireless PHY: Modulation and Demodulation Y. Richard Yang 09/11/2012 Outline Admin and recap Amplitude demodulation Digital modulation 2 Admin Assignment 1 posted 3 Recap: Modulation Objective o Frequency

More information

1. Clearly circle one answer for each part.

1. Clearly circle one answer for each part. TB 10-15 / Exam Style Questions 1 EXAM STYLE QUESTIONS Covering Chapters 10-15 of Telecommunication Breakdown 1. Clearly circle one answer for each part. (a) TRUE or FALSE: For two rectangular impulse

More information

Project 2. Project 2: audio equalizer. Fig. 1: Kinter MA-170 stereo amplifier with bass and treble controls.

Project 2. Project 2: audio equalizer. Fig. 1: Kinter MA-170 stereo amplifier with bass and treble controls. Introduction Project 2 Project 2: audio equalizer This project aims to motivate our study o ilters by considering the design and implementation o an audio equalizer. An equalizer (EQ) modiies the requency

More information

y(n)= Aa n u(n)+bu(n) b m sin(2πmt)= b 1 sin(2πt)+b 2 sin(4πt)+b 3 sin(6πt)+ m=1 x(t)= x = 2 ( b b b b

y(n)= Aa n u(n)+bu(n) b m sin(2πmt)= b 1 sin(2πt)+b 2 sin(4πt)+b 3 sin(6πt)+ m=1 x(t)= x = 2 ( b b b b Exam 1 February 3, 006 Each subquestion is worth 10 points. 1. Consider a periodic sawtooth waveform x(t) with period T 0 = 1 sec shown below: (c) x(n)= u(n). In this case, show that the output has the

More information

Spectrogram Review The Sampling Problem: 2π Ambiguity Fourier Series. Lecture 6: Sampling. ECE 401: Signal and Image Analysis. University of Illinois

Spectrogram Review The Sampling Problem: 2π Ambiguity Fourier Series. Lecture 6: Sampling. ECE 401: Signal and Image Analysis. University of Illinois Lecture 6: Sampling ECE 401: Signal and Image Analysis University of Illinois 2/7/2017 1 Spectrogram Review 2 The Sampling Problem: 2π Ambiguity 3 Fourier Series Outline 1 Spectrogram Review 2 The Sampling

More information

Signal Sampling. Sampling. Sampling. Sampling. Sampling. Sampling

Signal Sampling. Sampling. Sampling. Sampling. Sampling. Sampling Signal Let s sample the signal at a time interval o Dr. Christopher M. Godrey University o North Carolina at Asheville Photo: C. Godrey Let s sample the signal at a time interval o Reconstruct the curve

More information

6.02 Fall 2012 Lecture #12

6.02 Fall 2012 Lecture #12 6.02 Fall 2012 Lecture #12 Bounded-input, bounded-output stability Frequency response 6.02 Fall 2012 Lecture 12, Slide #1 Bounded-Input Bounded-Output (BIBO) Stability What ensures that the infinite sum

More information

PROBLEM SET 6. Note: This version is preliminary in that it does not yet have instructions for uploading the MATLAB problems.

PROBLEM SET 6. Note: This version is preliminary in that it does not yet have instructions for uploading the MATLAB problems. PROBLEM SET 6 Issued: 2/32/19 Due: 3/1/19 Reading: During the past week we discussed change of discrete-time sampling rate, introducing the techniques of decimation and interpolation, which is covered

More information

Experiment 7: Frequency Modulation and Phase Locked Loops Fall 2009

Experiment 7: Frequency Modulation and Phase Locked Loops Fall 2009 Experiment 7: Frequency Modulation and Phase Locked Loops Fall 2009 Frequency Modulation Normally, we consider a voltage wave orm with a ixed requency o the orm v(t) = V sin(ω c t + θ), (1) where ω c is

More information

3.1 Introduction to Modulation

3.1 Introduction to Modulation Haberlesme Sistemlerine Giris (ELE 361) 9 Eylul 2017 TOBB Ekonomi ve Teknoloji Universitesi, Guz 2017-18 Dr. A. Melda Yuksel Turgut & Tolga Girici Lecture Notes Chapter 3 Amplitude Modulation Speech, music,

More information

MATLAB Assignment. The Fourier Series

MATLAB Assignment. The Fourier Series MATLAB Assignment The Fourier Series Read this carefully! Submit paper copy only. This project could be long if you are not very familiar with Matlab! Start as early as possible. This is an individual

More information

McGill University. Department. of Electrical and Computer Engineering. Communications systems A

McGill University. Department. of Electrical and Computer Engineering. Communications systems A McGill University Department. o Electrical and Computer Engineering Communications systems 304-411A 1 The Super-heterodyne Receiver 1.1 Principle and motivation or the use o the super-heterodyne receiver

More information

EECS 455 Solution to Problem Set 3

EECS 455 Solution to Problem Set 3 EECS 455 Solution to Problem Set 3. (a) Is it possible to have reliably communication with a data rate of.5mbps using power P 3 Watts with a bandwidth of W MHz and a noise power spectral density of N 8

More information

EECS 216 Winter 2008 Lab 2: FM Detector Part I: Intro & Pre-lab Assignment

EECS 216 Winter 2008 Lab 2: FM Detector Part I: Intro & Pre-lab Assignment EECS 216 Winter 2008 Lab 2: Part I: Intro & Pre-lab Assignment c Kim Winick 2008 1 Introduction In the first few weeks of EECS 216, you learned how to determine the response of an LTI system by convolving

More information

Sampling of Continuous-Time Signals. Reference chapter 4 in Oppenheim and Schafer.

Sampling of Continuous-Time Signals. Reference chapter 4 in Oppenheim and Schafer. Sampling of Continuous-Time Signals Reference chapter 4 in Oppenheim and Schafer. Periodic Sampling of Continuous Signals T = sampling period fs = sampling frequency when expressing frequencies in radians

More information

EE 422G - Signals and Systems Laboratory

EE 422G - Signals and Systems Laboratory EE 422G - Signals and Systems Laboratory Lab 3 FIR Filters Written by Kevin D. Donohue Department of Electrical and Computer Engineering University of Kentucky Lexington, KY 40506 September 19, 2015 Objectives:

More information

Optimum Bandpass Filter Bandwidth for a Rectangular Pulse

Optimum Bandpass Filter Bandwidth for a Rectangular Pulse M. A. Richards, Optimum Bandpass Filter Bandwidth for a Rectangular Pulse Jul., 015 Optimum Bandpass Filter Bandwidth for a Rectangular Pulse Mark A. Richards July 015 1 Introduction It is well-known that

More information

Fall Music 320A Homework #2 Sinusoids, Complex Sinusoids 145 points Theory and Lab Problems Due Thursday 10/11/2018 before class

Fall Music 320A Homework #2 Sinusoids, Complex Sinusoids 145 points Theory and Lab Problems Due Thursday 10/11/2018 before class Fall 2018 2019 Music 320A Homework #2 Sinusoids, Complex Sinusoids 145 points Theory and Lab Problems Due Thursday 10/11/2018 before class Theory Problems 1. 15 pts) [Sinusoids] Define xt) as xt) = 2sin

More information

Nonlinear FM Waveform Design to Reduction of sidelobe level in Autocorrelation Function

Nonlinear FM Waveform Design to Reduction of sidelobe level in Autocorrelation Function 017 5 th Iranian Conerence on Electrical (ICEE) Nonlinear FM Waveorm Design to Reduction o sidelobe level in Autocorrelation Function Roohollah Ghavamirad Department o Electrical K. N. Toosi University

More information

Data Acquisition Systems. Signal DAQ System The Answer?

Data Acquisition Systems. Signal DAQ System The Answer? Outline Analysis of Waveforms and Transforms How many Samples to Take Aliasing Negative Spectrum Frequency Resolution Synchronizing Sampling Non-repetitive Waveforms Picket Fencing A Sampled Data System

More information

4. Design of Discrete-Time Filters

4. Design of Discrete-Time Filters 4. Design of Discrete-Time Filters 4.1. Introduction (7.0) 4.2. Frame of Design of IIR Filters (7.1) 4.3. Design of IIR Filters by Impulse Invariance (7.1) 4.4. Design of IIR Filters by Bilinear Transformation

More information

Massachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Fall Semester, Introduction to EECS 2

Massachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Fall Semester, Introduction to EECS 2 Massachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Fall Semester, 2006 6.082 Introduction to EECS 2 Modulation and Demodulation Introduction A communication system

More information

Solution of ECE 342 Test 3 S12

Solution of ECE 342 Test 3 S12 Solution of ECE 34 Test 3 S1 1 A random power signal has a mean of three and a standard deviation of five Find its numerical total average signal power Signal Power P = 3 + 5 = 34 A random energy signal

More information

6.976 High Speed Communication Circuits and Systems Lecture 16 Noise in Integer-N Frequency Synthesizers

6.976 High Speed Communication Circuits and Systems Lecture 16 Noise in Integer-N Frequency Synthesizers 6.976 High Speed Communication Circuits and Systems Lecture 16 in Integer-N Frequency Synthesizers Michael Perrott Massachusetts Institute o Technology Copyright 23 by Michael H. Perrott Frequency Synthesizer

More information

The Communications Channel (Ch.11):

The Communications Channel (Ch.11): ECE-5 Phil Schniter February 5, 8 The Communications Channel (Ch.): The eects o signal propagation are usually modeled as: ECE-5 Phil Schniter February 5, 8 Filtering due to Multipath Propagation: The

More information

George Mason University ECE 201: Introduction to Signal Analysis Spring 2017

George Mason University ECE 201: Introduction to Signal Analysis Spring 2017 Assigned: March 7, 017 Due Date: Week of April 10, 017 George Mason University ECE 01: Introduction to Signal Analysis Spring 017 Laboratory Project #7 Due Date Your lab report must be submitted on blackboard

More information

Digital modulations (part 1)

Digital modulations (part 1) Digital modulations (part 1) Outline : 1. Digital modulations definition. Classic linear modulations.1 Power spectral density. Amplitude digital modulation (ASK).3 Phase digital modulation (PSK).4 Quadrature

More information

Final Exam Practice Questions for Music 421, with Solutions

Final Exam Practice Questions for Music 421, with Solutions Final Exam Practice Questions for Music 4, with Solutions Elementary Fourier Relationships. For the window w = [/,,/ ], what is (a) the dc magnitude of the window transform? + (b) the magnitude at half

More information

Speech, music, images, and video are examples of analog signals. Each of these signals is characterized by its bandwidth, dynamic range, and the

Speech, music, images, and video are examples of analog signals. Each of these signals is characterized by its bandwidth, dynamic range, and the Speech, music, images, and video are examples of analog signals. Each of these signals is characterized by its bandwidth, dynamic range, and the nature of the signal. For instance, in the case of audio

More information

ECE5713 : Advanced Digital Communications

ECE5713 : Advanced Digital Communications ECE5713 : Advanced Digital Communications Bandpass Modulation MPSK MASK, OOK MFSK 04-May-15 Advanced Digital Communications, Spring-2015, Week-8 1 In-phase and Quadrature (I&Q) Representation Any bandpass

More information

Outline. Discrete time signals. Impulse sampling z-transform Frequency response Stability INF4420. Jørgen Andreas Michaelsen Spring / 37 2 / 37

Outline. Discrete time signals. Impulse sampling z-transform Frequency response Stability INF4420. Jørgen Andreas Michaelsen Spring / 37 2 / 37 INF4420 Discrete time signals Jørgen Andreas Michaelsen Spring 2013 1 / 37 Outline Impulse sampling z-transform Frequency response Stability Spring 2013 Discrete time signals 2 2 / 37 Introduction More

More information

ECE 201: Introduction to Signal Analysis. Dr. B.-P. Paris Dept. Electrical and Comp. Engineering George Mason University

ECE 201: Introduction to Signal Analysis. Dr. B.-P. Paris Dept. Electrical and Comp. Engineering George Mason University ECE 201: Introduction to Signal Analysis Dr. B.-P. Paris Dept. Electrical and Comp. Engineering George Mason University Last updated: November 29, 2016 2016, B.-P. Paris ECE 201: Intro to Signal Analysis

More information

Chapter 3 Digital Transmission Fundamentals

Chapter 3 Digital Transmission Fundamentals Chapter 3 Digital Transmission Fundamentals Characterization of Communication Channels Fundamental Limits in Digital Transmission CSE 323, Winter 200 Instructor: Foroohar Foroozan Chapter 3 Digital Transmission

More information

High Speed Communication Circuits and Systems Lecture 10 Mixers

High Speed Communication Circuits and Systems Lecture 10 Mixers High Speed Communication Circuits and Systems Lecture Mixers Michael H. Perrott March 5, 24 Copyright 24 by Michael H. Perrott All rights reserved. Mixer Design or Wireless Systems From Antenna and Bandpass

More information

EE 403: Digital Signal Processing

EE 403: Digital Signal Processing OKAN UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE 1 EEE 403 DIGITAL SIGNAL PROCESSING (DSP) 01 INTRODUCTION FALL 2012 Yrd. Doç. Dr. Didem Kıvanç Türeli didem.kivanc@okan.edu.tr EE 403: Digital Signal

More information