PEI101
DIGITAL SIGNAL PROCESSING TECHNIQUES 


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Prerequisite(s): None 
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.
Multirate 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.
Case Studies : Case studies on Temporal and
spatial signal processing.
Recommended Books