# lecture2 - EE 313 Linear Systems and Signals Fall 2010...

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Signals Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin EE 313 Linear Systems and Signals Fall 2010 Initial conversion of content to PowerPoint by Dr. Wade C. Schwartzkopf

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2-2 Course Outline Time domain analysis (lectures 1-10) Signals and systems in continuous and discrete time Convolution: finding system response in time domain Frequency domain analysis (lectures 11-16) Fourier series Fourier transforms Frequency responses of systems Generalized frequency domain analysis (lectures 17-26) Laplace and z transforms of signals Roberts, ch. 1-3 Roberts, ch. 4-7 Roberts, ch. 9-12
2-3 Signals A function, e.g. sin( t ) in continuous-time or sin(2 π n / 10) in discrete-time, useful in analysis A sequence of numbers, e.g. {1,2,3,2,1} which is a sampled triangle function, useful in simulation A collection of properties, e.g. even symmetric about origin, useful in reasoning about behavior A piecewise representation, e.g. A functional, e.g. the Dirac delta functional δ ( t ) ( 29 < = = 0 for 0 0 for 2 1 0 for 1 t t t t u = otherwise 0 0 for 1 ] [ n n u

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2-4 Exponential Signals Solutions to linear constant-coefficient differential equations, and hence, very common e t e - t t t t = -1 : 0.01 : 1; e1 = exp(t); plot(t, e1) t = -1 : 0.01 : 1; e2 = exp(-t); plot(t, e2)
2-5 Exponential Signal Properties Real-valued exponential signals Amplitude values are always non-negative Might decay or not as t goes to infinity Complex-valued exponential signals

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## This note was uploaded on 02/16/2011 for the course ECE 313 taught by Professor Evans during the Spring '11 term at University of Texas at Austin.

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lecture2 - EE 313 Linear Systems and Signals Fall 2010...

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