EC3492 DIGITAL SIGNAL PROCESSING Anna University Syllabus
EC3492 DIGITAL SIGNAL PROCESSING L T P C 3 0 2 4
COURSE OBJECTIVES:
● To learn discrete fourier transform, properties of DFT and its application to linear filtering
● To understand the characteristics of digital filters, design digital IIR and FIR filters and apply these filters to filter undesirable signals in various frequency bands
● To understand the effects of finite precision representation on digital filters
● To understand the fundamental concepts of multi rate signal processing and its applications
● To introduce the concepts of adaptive filters and its application to communication engineering
UNIT I DISCRETE FOURIER TRANSFORM 9
Sampling Theorem, concept of frequency in discrete-time signals, summary of analysis & synthesis equations for FT & DTFT, frequency domain sampling, Discrete Fourier transform (DFT) - deriving DFT from DTFT, properties of DFT - periodicity, symmetry, circular convolution. Linear filtering using DFT. Filtering long data sequences - overlap save and overlap add method. Fast computation of
DFT - Radix-2 Decimation-in-time (DIT) Fast Fourier transform (FFT), Decimation-in-frequency (DIF) Fast Fourier transform (FFT). Linear filtering using FFT.
UNIT II INFINITE IMPULSE RESPONSE FILTERS 9
Characteristics of practical frequency selective filters. characteristics of commonly used analog filters - Butterworth filters, Chebyshev filters. Design of IIR filters from analog filters (LPF, HPF, BPF, BRF) - Approximation of derivatives, Impulse invariance method, Bilinear transformation. Frequency transformation in the analog domain. Structure of IIR filter - direct form I, direct form II, Cascade, parallel realizations.
UNIT III FINITE IMPULSE RESPONSE FILTERS 9
Design of FIR filters - symmetric and Anti-symmetric FIR filters - design of linear phase FIR filters using Fourier series method - FIR filter design using windows (Rectangular, Hamming and Hanning window), Frequency sampling method. FIR filter structures - linear phase structure, direct form realizations
UNIT IV FINITE WORD LENGTH EFFECTS 9
Fixed point and floating point number representation - ADC - quantization - truncation and rounding - quantization noise - input / output quantization - coefficient quantization error - product quantization error - overflow error - limit cycle oscillations due to product quantization and summation - scaling to prevent overflow.
UNIT V DSP APPLICATIONS 9
Multirate signal processing: Decimation, Interpolation, Sampling rate conversion by a rational factor – Adaptive Filters: Introduction, Applications of adaptive filtering to equalization-DSP Architecture- Fixed and Floating point architecture principles
PRACTICAL EXERCISES:
MATLAB / EQUIVALENT SOFTWARE PACKAGE/ DSP PROCESSOR BASED
IMPLEMENTATION
1. Generation of elementary Discrete-Time sequences
2. Linear and Circular convolutions
3. Auto correlation and Cross Correlation
4. Frequency Analysis using DFT
5. Design of FIR filters (LPF/HPF/BPF/BSF) and demonstrates the filtering operation
6. Design of Butterworth and Chebyshev IIR filters (LPF/HPF/BPF/BSF) and demonstrate the filtering operations
7. Study of architecture of Digital Signal Processor
8. Perform MAC operation using various addressing modes
9. Generation of various signals and random noise
10. Design and demonstration of FIR Filter for Low pass, High pass, Band pass and Band stop filtering
11. Design and demonstration of Butter worth and Chebyshev IIR Filters for Low pass,High pass, Band pass and Band stop filtering
12. Implement an Up-sampling and Down-sampling operation in DSP Processor
COURSE OUTCOMES:
At the end of the course students will be able to:
CO1:Apply DFT for the analysis of digital signals and systems
CO2:Design IIR and FIR filters
CO3: Characterize the effects of finite precision representation on digital filters
CO4:Design multirate filters
CO5:Apply adaptive filters appropriately in communication systems
TEXT BOOKS:
1. 1.John G. Proakis and Dimitris G.Manolakis, Digital Signal Processing – Principles,
Algorithms and Applications, Fourth Edition, Pearson Education / Prentice Hall, 2007.
2. 2.A. V. Oppenheim, R.W. Schafer and J.R. Buck, ―Discrete-Time Signal Processing‖, 8th Indian Reprint, Pearson, 2004.
REFERENCES
1. Emmanuel C. Ifeachor& Barrie. W. Jervis, “Digital Signal Processing”, Second Edition, Pearson Education / Prentice Hall, 2002.
2. 2.Sanjit K. Mitra, “Digital Signal Processing – A Computer Based Approach”, Tata Mc Graw Hill, 2007.
3. 3.Andreas Antoniou, “Digital Signal Processing”, Tata Mc Graw Hill, 2006.
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