Course Details

Subject {L-T-P / C} : CS3305 : Digital Signal Processing { 3-0-0 / 3}

Subject Nature : Theory

Coordinator : Ratnakar Dash

Syllabus

UNIT -I: Signals and signal processing
Characterization and classification of signals, Typical signal processing operations, Typical signal processing applications, Advantages of digital signal processing,
UNIT -II: Time domain representations of signals and systems
Discrete time signals, Operations on sequences, discrete time systems, Linear time invariant discrete time systems, Characterization of LTI systems
UNIT-III: Transform domain representation of signals and systems
The discrete time Fourier transform, the frequency response, the transfer function, Discrete Fourier series, Discrete Fourier transform, Computation of DFT Linear convolution using DFT, The z-transform, The region of convergence of z-transform
UNIT -IV: Structures for discrete time systems
Block diagram and signal flow representation of constant coefficient linear difference equation, Basic structures for IIR systems, Basic structures for FIR systems, Lattice structures, Effects of coefficient quantization, Effect of round off noise in digital filters, Zero-input limit cycles
UNIT -V: Filter design techniques
Design of discrete time IIR filters from continuous time filters, Design of FIR filters by windowing, Optimum approximation of FIR filters, Linear phase filters
UNIT -VI: Sampling of continuous time signals
Periodic sampling, Frequency domain representation of sampling, Reconstruction of bandlimited signal from its samples, Discrete time processing of continuous time signals, Continuous time processing of discrete time signals, Changing the sampling rate using discrete time processing

Course Objectives

Course Outcomes

On successful completion of this course, the student will be able to:
1. formulate engineering problems in terms of DSP tasks
2. apply engineering problem solving strategies to DSP problems
3. design and test DSP algorithms
4. analyze digital and analog signals and systems
5. recover information from signals
6. encode information into signals
7. design digital signal processing algorithms
8. design and simulate digital filters

Essential Reading

Supplementary Reading