EE 309 Signal and Linear System Analysis

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1 Course Overview and Introduction

2 Course Overview Course Web Page: Directly: mercury.pr.erau.edu/~bruders/ Canvas Required Textbook: "Engineering Signals and Systems, 2nd Edition" by Fawwaz T. Ulaby and Andrew E. Yagle Software/Hardware Usage: MATLAB software and digilent Analog Discovery H/W Pre-Requisite: EE 223 and MA 345 Slide 2 of 15

3 Course Overview Lectures: MWF 10:00 a.m. - 10:50 a.m. in STEM 105 Labs: Tuesday 1:25-4:05 pm in STEM 110 Instructor: Dr. Stephen Bruder Office: King Eng. Rm bruders@erau.edu Office Hours: Labs start on Tuesday 4 th Sept. M,T,W,Th 8-9 am & M,T,W 4-5 pm Slide 3 of 15

4 Course Overview Course Description: This course includes discussions of signals and systems, convolution, continuous time signals, spectra of continuous time signals, time-domain and spectral analysis of continuous time signals, Laplace transforms, discrete time signals, spectra of discrete time signals, time-domain and spectral analysis of discrete time signals, and the Z- transform. Slide 4 of 15

5 Course Overview Course Objectives: Provide students with a basic understanding of how signals and linear systems interact Examine both continuous and discrete signals Analyze both continuous and discrete systems Lay the foundation for further studies in control, communications, signal processing, etc Grading Scheme: Homework Assignments 20% Two Mid-Term Exams 30% Final Exam 30% Labs 20% Slide 5 of 15

6 Course Overview Grading Scheme: Weekly homework assignments: 20 % o Homework will be assigned on a Mon/Wed and due the following Mon/Wed o Late submissions will NOT be accepted Two Mid-Term exams (Open book/notes): 30 % o Mid-Term exam #1: 1:25-3:25 pm Tue, Sept 25 in STEM 110 o Mid-Term exam #2: 1:25-3:25 pm Tue, Oct 30 in STEM 110 Final Exam (Open book/notes): 30 % o 10:15 a.m. to 12:15 p.m. on Thur, Dec 13 in in STEM 105 Labs: 20 % o Ten lab experiments (submission via CANVAS) Slide 6 of 15

7 Academic Integrity/Conduct Embry-Riddle is committed to maintaining and upholding intellectual integrity. All students, faculty, and staff have obligations to prevent violations of academic integrity and take corrective action when they occur. The adjudication process will include the sanction imposed on students who commit the following academic violations, which may include a failing grade on the assignment, a failing grade for the course, suspension, or dismissal from the University. 1. Plagiarism: Presenting as one s own the ideas, words, or products of another. Plagiarism includes use of any source to complete academic assignments without proper acknowledgment of the source. 2. Cheating is a broad term that includes the following: Giving or receiving help from unauthorized persons or materials during examinations. The unauthorized communication of examination questions prior to, during, or following administration of the examination. Collaboration on examinations or assignments expected to be individual work. Fraud and deceit, which include knowingly furnishing false or misleading information or failing to furnish appropriate information when requested, such as when applying for admission to the University. Slide 7 of 15

8 Course Outline Course Description Continuous time: o Signals: Properties, transformations, Basic types: Impulse, step, ramp, Fourier series Sampling theorem o Linear Systems: Response, properties, Convolution, Laplace Transform, Fourier transform, transfer function, Parseval s theorem Slide 8 of 15

9 Course Outline Course Description Discrete time: o Signals: Nyquist theorem and aliasing Properties, transformations, Difference equations o Linear Systems: Response, properties, Discrete Convolution, Z-Transform, Discrete Fourier transform, discrete transfer function, Filters Detailed Class Schedule: (from webpage) Slide 9 of 15

10 Introduction to Signals & Systems What is a signal? A signal can be a waveform which contains information o A force produced by an engine acting on a car o A voltage signal into (or out from) a circuit o An acoustic pressure wave incident on your eardrum Physical units of a signal depend on the area of application o E.g., V, ma, m/sec, Pa, C, Typically, signals vary with time (independent variable) Classification of Signals: ECG Signal o Signals can be causal, continuous, discrete, digital, periodic, Slide 10 of 15

11 Introduction to Signals & Systems What is a System? A system is a process or device that accepts an input signal to produce an output signal A system modifies or transforms signals o E.g., A microphone converts a sound pressure signal into an electrical signal Slide 11 of 15

12 Types of Signals Continuous vs Discrete vs Digital Causal vs Noncausal Causal Signal: Does NOT start before time t = 0 Noncausal Signal: Can start before time t = 0 8 Causal vs Noncausal Signals 6 f f (t) Causal Causal f NonCausal (t) (t) 4 2 f Causal () t = 0.33t 10 sin(0.62 π ) 0 e t t 0 t < 0 Magnitude MATLAB Code Lecture_01_cont_vs_discrete.m f t = π < < 0.33 ( ) 10 t NonCausal e sin( 0.62 t) t Time (sec) Slide 12 of 15

Types of Signals Continuous vs Discrete vs Digital Continuous vs Discrete vs Digital Continuous: Uniquely defined for all real values of t Discrete: Signal is defined only at

13 Types of Signals Continuous vs Discrete vs Digital Continuous vs Discrete vs Digital Continuous: Uniquely defined for all real values of t Discrete: Signal is defined only at tt = kkkk o i.e. discrete time Digital: Signal is discrete in both time and amplitude MATLAB Code Lecture_01_cont_vs_discrete.m f t e t 0.33t ( ) = 10 sin(0.62 π ) Slide 13 of 15

14 Types of Signals Continuous vs Discrete vs Digital Discrete vs Digital 7 10 = Slide 14 of 15

15 Next Lecture Signal Transformations Time-shift and time-scaling Reading Assignment: Chap Slide 15 of 15

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