EE 301: Signals and Systems (3)
Upon the completion of this course students should be able to:
- Understand the fundamental properties of linear time invariant systems
- Understand and use linear systems tools including transform analysis
- Analyze and predict the behavior of linear system
Introduction to the Course and Basic Concepts; Signals & their Transformation; Elementary Signals in the Continuous and Discrete Time Domains; Classification of Systems; Properties of Linear Time Invariant Systems; Convolution, Invertibility, Stability and Causality; Unit Step and Impulse Responses; Systems Described by Differential & Difference Equations; Fourier Series; Introduction to Fourier Transform for Continuous Time signals; Fourier Transform of Periodic Functions; Fourier Transform Properties; Fourier Analysis of Discrete Time Signals & Systems; Properties of DTFT; Convolution, Modulation & Other Properties of DTFT; Introduction to Sampling; Spectrum of Sampled Signals, Aliasing; Introduction to Laplace Transform; Properties of Laplace Transform; Introduction to Z Transform; Properties of Z Transform; Introduction to Random Signals & Probability; Probability Functions; PD(Distribution)F & pd(density)f; Classification of Random Processes; Correlation Functions; Spectral Density; Response of Linear Systems to Random Inputs; Frequency Domain Analysis of LTI Systems Excited by Random Inputs.
- Signals and Systems, A V Oppenheim, A S Willsky, and S H Nawab, 2nd Edition, PHI Learning Pvt. Ltd, New Delhi
|Previous||Back to Course List||Next|