EE6403 DISCRETE TIME SYSTEMS AND SIGNAL PROCESSING L T P C 3 0 0 3
OBJECTIVES:
• To classify signals and systems & their mathematical representation.
• To analyse the discrete time systems.
• To study various transformation techniques & their computation.
• To study about filters and their design for digital implementation.
• To study about a programmable digital signal processor & quantization effects.
UNIT I INTRODUCTION 9
Classification of systems: Continuous, discrete, linear, causal, stable, dynamic, recursive, time variance; classification of signals: continuous and discrete, energy and power; mathematical representation of signals; spectral density; sampling techniques, quantization, quantization error, Nyquist rate, aliasing effect.
UNIT II DISCRETE TIME SYSTEM ANALYSIS 9
Z-transform and its properties, inverse z-transforms; difference equation – Solution by z- transform,application to discrete systems - Stability analysis, frequency response – Convolution – Discrete TimeFourier transform , magnitude and phase representation.
UNIT III DISCRETE FOURIER TRANSFORM & COMPUTATION 9
Discrete Fourier Transform- properties, magnitude and phase representation - Computation of DFT
using FFT algorithm – DIT &DIF using radix 2 FFT – Butterfly structure.
UNIT IV DESIGN OF DIGITAL FILTERS 9
FIR & IIR filter realization – Parallel & cascade forms. FIR design: Windowing Techniques – Need and choice of windows – Linear phase characteristics. Analog filter design – Butterworth and Chebyshev approximations; IIR Filters, digital design using impulse invariant and bilinear transformation - mWarping, pre warping.
UNIT V DIGITAL SIGNAL PROCESSORS 9
Introduction – Architecture – Features – Addressing Formats – Functional modes - Introduction to
Commercial DSProcessors.
TOTAL : 45 PERIODS
OUTCOMES:
• Ability to understand and apply basic science, circuit theory, Electro-magnetic field theory control theory and apply them to electrical engineering problems.
TEXT BOOKS:
1. J.G. Proakis and D.G. Manolakis, ‘Digital Signal Processing Principles, Algorithms and Applications’, Pearson Education, New Delhi, PHI. 2003.
2. S.K. Mitra, ‘Digital Signal Processing – A Computer Based Approach’, McGraw
Hill Edu, 2013.
3. Robert Schilling & Sandra L.Harris, Introduction to Digital Signal Processing using Matlab”, Cengage Learning,2014.
REFERENCES:
1. Poorna Chandra S, Sasikala. B ,Digital Signal Processing, Vijay Nicole/TMH,2013.
2. B.P.Lathi, ‘Principles of Signal Processing and Linear Systems’, Oxford University Press, 2010
3. Taan S. ElAli, ‘Discrete Systems and Digital Signal Processing with Mat Lab’, CRC Press, 2009.
4. Sen M.kuo, woonseng…s.gan, “Digital Signal Processors, Architecture, Implementations & Applications, Pearson,2013
5. Dimitris G.Manolakis, Vinay K. Ingle, applied Digital Signal Processing,Cambridge,2012
6. Lonnie C.Ludeman ,”Fundamentals of Digital Signal Processing”,Wiley,2013
OBJECTIVES:
• To classify signals and systems & their mathematical representation.
• To analyse the discrete time systems.
• To study various transformation techniques & their computation.
• To study about filters and their design for digital implementation.
• To study about a programmable digital signal processor & quantization effects.
UNIT I INTRODUCTION 9
Classification of systems: Continuous, discrete, linear, causal, stable, dynamic, recursive, time variance; classification of signals: continuous and discrete, energy and power; mathematical representation of signals; spectral density; sampling techniques, quantization, quantization error, Nyquist rate, aliasing effect.
UNIT II DISCRETE TIME SYSTEM ANALYSIS 9
Z-transform and its properties, inverse z-transforms; difference equation – Solution by z- transform,application to discrete systems - Stability analysis, frequency response – Convolution – Discrete TimeFourier transform , magnitude and phase representation.
UNIT III DISCRETE FOURIER TRANSFORM & COMPUTATION 9
Discrete Fourier Transform- properties, magnitude and phase representation - Computation of DFT
using FFT algorithm – DIT &DIF using radix 2 FFT – Butterfly structure.
UNIT IV DESIGN OF DIGITAL FILTERS 9
FIR & IIR filter realization – Parallel & cascade forms. FIR design: Windowing Techniques – Need and choice of windows – Linear phase characteristics. Analog filter design – Butterworth and Chebyshev approximations; IIR Filters, digital design using impulse invariant and bilinear transformation - mWarping, pre warping.
UNIT V DIGITAL SIGNAL PROCESSORS 9
Introduction – Architecture – Features – Addressing Formats – Functional modes - Introduction to
Commercial DSProcessors.
TOTAL : 45 PERIODS
OUTCOMES:
• Ability to understand and apply basic science, circuit theory, Electro-magnetic field theory control theory and apply them to electrical engineering problems.
TEXT BOOKS:
1. J.G. Proakis and D.G. Manolakis, ‘Digital Signal Processing Principles, Algorithms and Applications’, Pearson Education, New Delhi, PHI. 2003.
2. S.K. Mitra, ‘Digital Signal Processing – A Computer Based Approach’, McGraw
Hill Edu, 2013.
3. Robert Schilling & Sandra L.Harris, Introduction to Digital Signal Processing using Matlab”, Cengage Learning,2014.
REFERENCES:
1. Poorna Chandra S, Sasikala. B ,Digital Signal Processing, Vijay Nicole/TMH,2013.
2. B.P.Lathi, ‘Principles of Signal Processing and Linear Systems’, Oxford University Press, 2010
3. Taan S. ElAli, ‘Discrete Systems and Digital Signal Processing with Mat Lab’, CRC Press, 2009.
4. Sen M.kuo, woonseng…s.gan, “Digital Signal Processors, Architecture, Implementations & Applications, Pearson,2013
5. Dimitris G.Manolakis, Vinay K. Ingle, applied Digital Signal Processing,Cambridge,2012
6. Lonnie C.Ludeman ,”Fundamentals of Digital Signal Processing”,Wiley,2013
