EC6502 PRINCIPLES OF DIGITAL SIGNAL PROCESSING syllabus-subject-notes-pevious-year-questions-papers-bank
OBJECTIVES:
To learn discrete Fourier transform and its properties
To know the characteristics of IIR and FIR filters learn the design of infinite and finite impulse response filters for filtering undesired signals
To understand Finite word length effects
To study the concept of Multirate and adaptive filters
UNIT I DISCRETE FOURIER TRANSFORM 9 Discrete Signals and Systems- A Review – Introduction to DFT – Properties of DFT – Circular Convolution - Filtering methods based on DFT – FFT Algorithms –Decimation in time Algorithms, Decimation in frequency Algorithms – Use of FFT in Linear Filtering.
UNIT II IIR FILTER DESIGN 9 Structures of IIR – Analog filter design – Discrete time IIR filter from analog filter – IIR filter design by Impulse Invariance, Bilinear transformation, Approximation of derivatives – (LPF, HPF, BPF, BRF) filter design using frequency translation.
UNIT III FIR FILTER DESIGN 9 Structures of FIR – Linear phase FIR filter – Fourier Series - Filter design using windowing techniques (Rectangular Window, Hamming Window, Hanning Window), Frequency sampling techniques – Finite word length effects in digital Filters: Errors, Limit Cycle, Noise Power Spectrum.
UNIT IV FINITE WORDLENGTH EFFECTS 9 Fixed point and floating point number representations – ADC –Quantization- Truncation and Rounding errors - Quantization noise – coefficient quantization error – Product quantization error - Overflow error – Roundoff noise power - limit cycle oscillations due to product round off and overflow errors – Principle of scaling
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.
OUTCOMES: Upon completion of the course, students will be able to
apply DFT for the analysis of digital signals & systems
design IIR and FIR filters
characterize finite Word length effect on filters
design the Multirate Filters
apply Adaptive Filters to equalization
TEXT BOOK:
1. John G. Proakis & Dimitris G.Manolakis, “Digital Signal Processing – Principles, Algorithms & Applications”, Fourth Edition, Pearson Education / Prentice Hall, 2007.
REFERENCES:
1. Emmanuel C..Ifeachor, & Barrie.W.Jervis, “Digital Signal Processing”, Second Edition, Pearson Education / Prentice Hall, 2002.
2. Sanjit K. Mitra, “Digital Signal Processing – A Computer Based Approach”, Tata Mc Graw Hill, 2007.
3. A.V.Oppenheim, R.W. Schafer and J.R. Buck, “Discrete-Time Signal Processing”, 8th Indian Reprint, Pearson, 2004.
4. Andreas Antoniou, “Digital Signal Processing”, Tata Mc Graw Hill, 2006.
OBJECTIVES:
To learn discrete Fourier transform and its properties
To know the characteristics of IIR and FIR filters learn the design of infinite and finite impulse response filters for filtering undesired signals
To understand Finite word length effects
To study the concept of Multirate and adaptive filters
UNIT I DISCRETE FOURIER TRANSFORM 9 Discrete Signals and Systems- A Review – Introduction to DFT – Properties of DFT – Circular Convolution - Filtering methods based on DFT – FFT Algorithms –Decimation in time Algorithms, Decimation in frequency Algorithms – Use of FFT in Linear Filtering.
UNIT II IIR FILTER DESIGN 9 Structures of IIR – Analog filter design – Discrete time IIR filter from analog filter – IIR filter design by Impulse Invariance, Bilinear transformation, Approximation of derivatives – (LPF, HPF, BPF, BRF) filter design using frequency translation.
UNIT III FIR FILTER DESIGN 9 Structures of FIR – Linear phase FIR filter – Fourier Series - Filter design using windowing techniques (Rectangular Window, Hamming Window, Hanning Window), Frequency sampling techniques – Finite word length effects in digital Filters: Errors, Limit Cycle, Noise Power Spectrum.
UNIT IV FINITE WORDLENGTH EFFECTS 9 Fixed point and floating point number representations – ADC –Quantization- Truncation and Rounding errors - Quantization noise – coefficient quantization error – Product quantization error - Overflow error – Roundoff noise power - limit cycle oscillations due to product round off and overflow errors – Principle of scaling
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.
OUTCOMES: Upon completion of the course, students will be able to
apply DFT for the analysis of digital signals & systems
design IIR and FIR filters
characterize finite Word length effect on filters
design the Multirate Filters
apply Adaptive Filters to equalization
TEXT BOOK:
1. John G. Proakis & Dimitris G.Manolakis, “Digital Signal Processing – Principles, Algorithms & Applications”, Fourth Edition, Pearson Education / Prentice Hall, 2007.
REFERENCES:
1. Emmanuel C..Ifeachor, & Barrie.W.Jervis, “Digital Signal Processing”, Second Edition, Pearson Education / Prentice Hall, 2002.
2. Sanjit K. Mitra, “Digital Signal Processing – A Computer Based Approach”, Tata Mc Graw Hill, 2007.
3. A.V.Oppenheim, R.W. Schafer and J.R. Buck, “Discrete-Time Signal Processing”, 8th Indian Reprint, Pearson, 2004.
4. Andreas Antoniou, “Digital Signal Processing”, Tata Mc Graw Hill, 2006.
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