PEI106: DIGITAL SIGNAL PROCESSING AND TECHNIQUES
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4.5 |
Course Objective: To understand the concepts, classifications and properties of discrete time signals and systems, to understand frequency domain analysis, awareness about filter designing and structure.
Discrete Time Signals and Systems: Introduction, Discrete time signals as array of values, Standard discrete time signals, Classification of discrete time signals, Discrete time systems and their classifications, Linear Time Invariant (LTI) Systems, Difference Equations: Finite Impulse Response (FIR) systems, Infinite Impulse Response (IIR) systems, Nonrecursive Systems and Recursive Systems and representation of discrete time systems via difference equations, Correlation: Crosscorrelation and Autocorrelation and their properties, Analog to Digital (A/D) Conversion: Sampling, Frequency Relationships, Aliasing, Quantization, Encoding, Sampling Theorem and Anti-Aliasing Filter.
The zTransforms: Introduction, ztransform, Properties of ztransform, Inverse ztransform, System function and Polezero plots from ztransform, Causality and Stability in terms of ztransform, Bilateral ztransform, Computation of ztransform
Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT): Discrete Fourier Transform and its Properties, Efficient Computation of DFT using FFT algorithms: Direct computation of the DFT, Divide and Conquer Approach, Radix2 and Radix4 FFT algorithms, Linear Filtering Approach to Computation of DFT.
Digital Filter Structure: Describing Equation of digital filter, Structures for FIR Systems: Direct Form Structure, Cascade Form Structure, Frequency Sampling Structure and Lattice Structure, Structure for IIR Systems: Direct Form Structures (FormI and FormII), Cascade Form Structure, Parallel Form Structure and Lattice Structure, Representation of Structures using Signal Flow Graph.
Design of Digital Filters: Characteristics of Practical Frequency Selective Filters, Design of FIR Filters using Windows: Rectangular, Bartlett, Hanning, Hamming and Blackman, Design of IIR Filters from Analog Filters, Frequency Transformations.
Multi-rate Digital Signal Processing: Introduction, Decimation by factor D, multistage implementation of sampling rate conversion, sampling rate conversion of bandpass filters.
Optimum Filters: Introduction, Forward and backward predictions, AR lattice and ARMA lattice ladder filters, Wiener filters for filtering and prediction.
Laboratory Work:
Calculation of Z transform, Calculation of Fourier transform, Design of FIR and IIR filters, Multi-rate signal processing, Design of optimum filters, realization of prediction.
Minor Project:
1. Case studies related to use of DSP application in instrumentation.
Application of DSP algorithms to condition signal from sensors.
Course Learning Outcomes (CLO):
After the completion of the course the students will be able to
1. Identifyvarious type of discrete signal.
2. Recognisevarious types of systems.
3. Analysefrequency domain response of systems.
4. Design varioustype of filter.
5. Implement filter structures.
Recommended Books:
1. Proakis, J.G. and Manolakis, D.K., Digital Signal Processing, Prentice Hall of India (2006).
2. Rabiner, Lawrence R. and Gold, B., Theory and Applications of Digital Signal Processing, Prentice Hall of India (2000).