DIGITAL SIGNAL PROCESSING 10CS752

The Eduladder is a community of students, teachers, and programmers just interested to make you pass any exams. So we solve previous year question papers for you.
See Our team
Wondering how we keep quality?
Got unsolved questions?

Ask Questions

You are here:Open notes-->VTU-->DIGITAL-SIGNAL-PROCESSING-10CS752-

DIGITAL SIGNAL PROCESSING 10CS752

How to study this subject


Subject Code: 10CS752 I.A. Marks : 25
Hours/Week : 04 Exam Hours: 03
Total Hours : 52 Exam Marks: 100
PART - A
UNIT – 1 7 Hours
The Discrete Fourier Transform: Its Properties and Applications :
Frequency Domain Sampling: The Discrete Fourier Transform: Frequency
Domain Sampling and Reconstruction of Discrete-Time Signals, The
Discrete Fourier Transform (DFT), The DFT as a Linear Transformation,
Relationship of the DFT to other Transforms. Properties of the DFT:
Periodicity, Linearity and Symmetry Properties, Multiplication of Two
DFT’s and Circular Convolution, Additional DFT Properties; Linear Filtering 77
Methods Based on the DFT: Use of the DFT in Linear Filtering, Filtering of
Long Data Sequences; Frequency Analysis of Signals using the DFT.
UNIT – 2 7 Hours
Efficient Computation of the DFT: Fast Fourier Transform Algorithms:
Efficient Computation of the DFT: FFT Algorithms : Direct Computation of
the DFT, Divide-and-Conquer Approach to Computation of the DFT, Radix-
2 FFT Algorithms, Radix-4 FFT Algorithms, Split-Radix FFT Algorithms,
Implementation of FFT Algorithms.
Applications of FFT Algorithms: Efficient computation of the DFT of Two
Real Sequences, Efficient computation of the DFT of a 2N-Point Real
Sequence, Use of the FFT Algorithm in Linear filtering and Correlation.
A Linear filtering approach to Computation of the DFT: The Goertzel
Algorithm, The Chirp-Z Transform Algorithm.
Quantization Effects in the Computation of the DFT: Quantization Errors in
the Direct Computation of the DFT, Quantization Errors in FFT Algorithms.
UNIT – 3 6 Hours
Implementation of Discrete-Time Systems – 1: Structures for the
Realization of Discrete-Time Systems
Structures for FIR Systems: Direct-Form Structures, Cascade-Form
Structures, Frequency-Sampling Structures, Lattice Structure.
Structures for IIR Systems: Direct-Form Structures, Signal Flow Graphs and
Transposed Structures, Cascade-Form Structures, Parallel-Form Structures,
Lattice and Lattice-Ladder Structures for IIR Systems.
UNIT – 4 6 Hours
Implementation of Discrete-Time Systems – 2: State-Space System
Analysis and Structures: State-Space Descriptions of Systems Characterized
by Difference Equations, Solution of the State-Space Equations, Relationships
between Input-Output and State-Space Descriptions, State-Space Analysis in
the Z-Domain, Additional State-Space Structures.
Representation of Numbers: Fixed-Point Representation of Numbers, Binary
Floating-Point Representation of Numbers, Errors Resulting from Rounding
and Truncation.
PART – B
UNIT – 5 6 Hours
Implementation of Discrete-Time Systems – 3: Quantization of Filter
Coefficients: Analysis of Sensitivity to Quantizatior of Filter Coefficients,
Quantization of Coefficients in FIR Filters78
Round-Off Effects in Digital Filters: Limit-Cycle Oscillations in Recursive
Systems, Scaling to Prevent Overflow, Statistical Characterization of
Quantization effects in Fixed-Point Realizations of Digital Filters.
UNIT – 6 7 Hours
Design of Digital Filters – 1: General Considerations: Causality and its
Implications, Characteristics of Practical Frequency-Selective Filters.
Design of FIR Filters: Symmetric And Antisymetric FIR Filters, Design of
Linear-Phase FIR Filters Using Windows, Design of Linear-Phase FIR Filters
by the Frequency-Sampling Method, Design of Optimum Equiripple LinearPhase
FIR Filters, Design of FIR Differentiators, Design of Hilbert
Transformers, Comparison of Design Methods for Linear-Phase FIR filters.
UNIT – 7 6 Hours
Design of Digital Filters – 2: Design of IIR Filters from Analog Filters: IIR
Filter Design by Approximation of Derivatives, IIR Filter Design by Impulse
Invariance, IIR Filter Design by the Bilinear Transformation, The Matched-Z
Transformation, Characteristics of commonly used Analog Filters, Some
examples of Digital Filters Designs based on the Bilinear Transformation.
UNIT – 8 7 Hours
Design of Digital Filters – 3: Frequency Transformations: Frequency
Transformations in the Analog Domain, Frequency Transformations in the
Digital Domain.
Design of Digital Filters based on Least-Squares method: Padι
Approximations method, Least-Square design methods, FIR least-Squares
Inverse (Wiener) Filters, Design of IIR Filters in the Frequency domain.
Text Books:
1. John G. Proakis and Dimitris G. Manolakis: Digital Signal
Processing, 3rd Edition, Pearson Education, 2003.
(Chapters 5, 6, 7 and 8)
Reference Books:
1. Paulo S. R. Diniz, Eduardo A. B. da Silva And Sergio L. Netto:
Digital Signal Processing: System Analysis and Design, Cambridge
University Press, 2002.
2. Sanjit K. Mitra: Digital Signal Processing: A Computer Based
Approach, Tata Mcgraw-Hill, 2001.
3. Alan V Oppenheim and Ronald W Schafer: Digital Signal
Processing, PHI, Indian Reprint, 2008. 


Official Notes


Add contents here

Notes from other sources


Add contents here

Model question papers


Add contents here

Previous year question papers


Add contents here

Useful links


Add contents here

Editors

arunwebberarunwebberarunwebberarunwebber


Join eduladder!