DIGITAL SIGNAL ANALYSIS AND PROCESSING
CT….
Lecture :
3 year : IV
Tutorial : 1 Part : I
Practical : 3/2
Course
Objectives:
1.
Discrete
time signals and systems [8
hours]
1.1. Discrete
time signal, basic signal types
1.2. Energy
signal, power signal
1.3. Periodicity
of discrete time signal
1.4. Transformation
of independent variable
1.5. Discrete
time Fourier series and properties
1.6. Discrete
time Fourier transform and properties
1.7. Discrete
time system properties
1.8. Linear
time invariant (LTI) system convolution sum, properties of LTI system
1.9. Frequency
response of LTI system
1.10. Sampling
of continuous time signal, spectral properties of sampled signal.
2.
Z-transform [4
hours]
2.1. 2.1
Defintion, convergence of Z-transform and region of convergence
2.2. 2.2
Properties of Z-transform (linearity, time shift, multiplication by exponential
sequence, differentiation, time reversal, convolution, multiplication)
2.3. 2.3
Inverse z-transform by long division and partial fraction expansion.
3.
Analysis
of LTI system in frequency domain [6
hours]
3.1. Frequency
response of LTI system, response to complex exponential
3.2. Linear
constant co-efficient difference equation and corresponding system function
3.3. Relationship
of frequency response to pole-zero of system
3.4. Linear
phase of LTI system and its relationship to causality.
4.
Discrete
filter structures [8
hours]
4.1. FIR
filter, Structures for FIR filter (direct form, cascade, frequency sampling,
lattice)
4.2. IIR
filter, structures for IIR filter (direct form I, direct form II, cascade,
lattice, lattice ladder)
4.3. Quantization
effect ( truncation, rounding), limit cycles and scaling.
5.
FIR filter
design [6
hours]
5.1. 5.1 Filter
design by window method, commonly used windows ( rectangular window, Hanning
window, Hamming window)
5.2. 5.2 Filter design by Kaiser window
5.3. 5.3 Filter design by frequency sampling method
5.4. 5.4 Filter design using optimum approximation,
Remez exchange algorithm.
6.
IIR filter
design 6
[hours]
6.1. Filter
design by impulse invariance method
6.2. Filter
design using bilinear transformation
6.3. Design of
digital low pass Butterworth filter
6.4. Properties
of Chebyshev filter, properties of elliptic filter, properties of Bessel
filter, Spectral transformation.
7.
Discrete
Fourier transform [7
hours]
7.1. Discrete
Fourier transform (DFT) representation, properties of DFT (linearity, time
shift, frequency shift, conjugation and conjugate symmetry, duality,
convolution, multiplication), circular convolution
7.2. Fast
Fourier Transform (FFT) algorithm (decimation in time algorithm, decimation in
frequency algorithm)
7.3. Computational
complexity of FFT algorithm.
Practical:
1.
Introduction
to DSP tools.
2.
Signal
generation and manipulation
3.
Convolution
4.
Cascade
of second order systems
5.
IIR filter
6.
FIR filter
References
1. Alan V. Oppenheim, Ronald W. Schafer, John R.
Buck, “Discrete-Time Signal Processing”, Pearson
Education.
2. John G.
Proakis, Dimitris G. Manolakis, “Digital Signal Processing”, Prentice Hall.
Evaluation Scheme
Marks
distribution for all the chapters in the syllabus is shown in the table below.
Unit
|
Hours
|
Mark Distribution*
|
1
|
8
|
9
|
2
|
4
|
6
|
3
|
6
|
10
|
4
|
8
|
10
|
5
|
6
|
15
|
6
|
6
|
15
|
7
|
7
|
15
|
Total
|
45
|
80
|
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