EC 1361 DIGITAL SIGNAL PROCESSING 3 1 0 100

AIM

To introduce the concept of analyzing discrete time signals & systems in the time

and frequency domain.

OBJECTIVES

i. To classify signals and systems & their mathematical representation.

ii. To analyse the discrete time systems.

iii. To study various transformation techniques & their computation.

iv. To study about filters and their design for digital implementation.

v. To study about a programmable digital signal processor &

quantization effects.

1. 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. Digital signal representation, analog to digital conversion.

2. 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 – Fourier transform of discrete sequence – Discrete Fourier series.

3. DISCRETE FOURIER TRANSFORM & COMPUTATION 9

DFT properties, magnitude and phase representation - Computation of DFT using FFT algorithm – DIT & DIF - FFT using radix 2 – Butterfly structure.

4. DESIGN OF DIGITAL FILTERS 9

FIR & IIR filter realization – Parallel & cascade forms. FIR design: Windowing Techniques – Need and choice of windows – Linear phase characteristics.

IIR design: Analog filter design - Butterworth and Chebyshev approximations; digital design using impulse invariant and bilinear transformation - Warping, prewarping - Frequency transformation.

5. PROGRAMMABLE DSP CHIPS 9

Architecture and features of TMS 320C54 signal processing chip – Quantisation effects in designing digital filters.

L = 45 T = 15 Total = 60

TEXT BOOKS

1. J.G. Proakis and D.G. Manolakis, ‘Digital Signal Processing Principles, Algorithms and Applications’, Pearson Education, New Delhi, 2003 / PHI.

2. S.K. Mitra, ‘Digital Signal Processing – A Computer Based Approach’, Tata McGraw Hill, New Delhi, 2001.

REFERENCE BOOKS

1. Alan V. Oppenheim, Ronald W. Schafer and John R. Buck, ‘Discrete – Time Signal Processing’, Pearson Education, New Delhi, 2003.

2. B. Venkataramani, M. Bhaskar, ‘Digital Signal Processors, Architecture, Programming and Applications’, Tata McGraw Hill, New Delhi, 2003.

3. S. Salivahanan, A. Vallavaraj, C. Gnanapriya, ‘Digital Signal Processing’, Tata McGraw Hill, New Delhi, 2003.

4. Texas TMS 320C54X user manual (website).

AIM

To introduce the concept of analyzing discrete time signals & systems in the time

and frequency domain.

OBJECTIVES

i. To classify signals and systems & their mathematical representation.

ii. To analyse the discrete time systems.

iii. To study various transformation techniques & their computation.

iv. To study about filters and their design for digital implementation.

v. To study about a programmable digital signal processor &

quantization effects.

1. 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. Digital signal representation, analog to digital conversion.

2. 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 – Fourier transform of discrete sequence – Discrete Fourier series.

3. DISCRETE FOURIER TRANSFORM & COMPUTATION 9

DFT properties, magnitude and phase representation - Computation of DFT using FFT algorithm – DIT & DIF - FFT using radix 2 – Butterfly structure.

4. DESIGN OF DIGITAL FILTERS 9

FIR & IIR filter realization – Parallel & cascade forms. FIR design: Windowing Techniques – Need and choice of windows – Linear phase characteristics.

IIR design: Analog filter design - Butterworth and Chebyshev approximations; digital design using impulse invariant and bilinear transformation - Warping, prewarping - Frequency transformation.

5. PROGRAMMABLE DSP CHIPS 9

Architecture and features of TMS 320C54 signal processing chip – Quantisation effects in designing digital filters.

L = 45 T = 15 Total = 60

TEXT BOOKS

1. J.G. Proakis and D.G. Manolakis, ‘Digital Signal Processing Principles, Algorithms and Applications’, Pearson Education, New Delhi, 2003 / PHI.

2. S.K. Mitra, ‘Digital Signal Processing – A Computer Based Approach’, Tata McGraw Hill, New Delhi, 2001.

REFERENCE BOOKS

1. Alan V. Oppenheim, Ronald W. Schafer and John R. Buck, ‘Discrete – Time Signal Processing’, Pearson Education, New Delhi, 2003.

2. B. Venkataramani, M. Bhaskar, ‘Digital Signal Processors, Architecture, Programming and Applications’, Tata McGraw Hill, New Delhi, 2003.

3. S. Salivahanan, A. Vallavaraj, C. Gnanapriya, ‘Digital Signal Processing’, Tata McGraw Hill, New Delhi, 2003.

4. Texas TMS 320C54X user manual (website).

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