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Digital Signal Processing: Beg 433 Ec

This document provides an overview of a course on digital signal processing. [1] It covers topics like discrete signals and systems, the discrete Fourier transform, the Z-transform, frequency response of difference equations, digital filter design including FIR and IIR filters, and digital filter implementation. [2] The course objectives are to introduce concepts like discrete signals, convolution, sampling, the DFT, Z-transform, filter design techniques, and filter implementations. [3] Labs focus on digital signal properties, response of recursive filters, and effects of quantization and finite precision in digital filters.

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Saroj Timsina
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106 views2 pages

Digital Signal Processing: Beg 433 Ec

This document provides an overview of a course on digital signal processing. [1] It covers topics like discrete signals and systems, the discrete Fourier transform, the Z-transform, frequency response of difference equations, digital filter design including FIR and IIR filters, and digital filter implementation. [2] The course objectives are to introduce concepts like discrete signals, convolution, sampling, the DFT, Z-transform, filter design techniques, and filter implementations. [3] Labs focus on digital signal properties, response of recursive filters, and effects of quantization and finite precision in digital filters.

Uploaded by

Saroj Timsina
Copyright
© Attribution Non-Commercial (BY-NC)
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOC, PDF, TXT or read online on Scribd
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DIGITAL SIGNAL PROCESSING

BEG 433 EC .Year: IV Teaching Schedule Hours/Week Theory Tutorial Practical 3 3/2 * Continuous ** Duration: 3 hours Course objectives: To provide 1. Discrete signals 1.1 Discrete signals unit impulse, unit step, exponential sequences 1.2 Linearity, shift invariance, causality 1.3 Convolution summation and discrete systems, response to discrete inputs 1.4 Stability sum and convergence of power series 1.5 Sampling continuous signals spectral properties of sampled signals The discrete Fourier transforms 2.1 The discrete Fourier transform (DFT) derivation 2.2 Properties of the DFT, DFT of non-periodic data 2.3 Introduction of the fast fourier transform (FFT) 2.4 Power spectral density using DFT/FFT algorithms Z transform 3.1 Definition of Z transform one sided and two sided transforms 3.2 Region of convergence relationship to causality 3.3 Inverse Z transform by long division, by partial fraction expansion. 3.4 Z transform properties delay advance, convolution, Parsevals theorem 3.5 Z transforn transfer function H (Z) transient and steady state sinusoidal response pole zero relationships, stability 3.6 General form of the linear, shift invariant constant coefficient difference equation 3.7 Z transform of difference equation. Frequency response 4.1 Steady state sinusoidal frequency response derived directly from the difference equation 4.2 Pole zero diagrams and frequency response 4.3 Design of a notch filter from the pole zero diagram. 5 Semester: II Examination Scheme Internal Assessment Theory Practical* 20 25 Final Theory Practical** 80 Total 125

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Discrete filters 6 5.1 Discrete filters structures, second order sections ladder filters frequency response 5.2 Digital filters finite precision implementations of discrete filters 5.3 Scaling and noise in digital filters, finite quantized signals quantization error linear models.

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HR Filter Design 7 6.1 Classical filter design using polynomial approximations Butterworth Chebishev 6.2 HR filter design by transformation matched Z transform impulse, invariant transform and bilinear transformation 6.3 Application of the bilinear transformation to HR low pass discrete filter design 6.4 Spectral transformations, high pass, band pass and notch filters. FIR Filter Design 3 7.1 FIR filter design by fourier approximation the complex fourier series 7.2 Gibbs phenomena in FIR filter design approximations, applications of window Functions to frequency response smoothing rectangular hanning Hamming and Kaiser windows. 7.3 FIR filter design by the frequency sampling method 7.4 FIR filter design using the Remez exchange algorithm Digital filter Implementation 8.1 Implementations using special purpose DSP processors, the Texas Instruments TMS320. 8.2 Bit serial arithmetic distributed arithmetic implementations, pipelined implementations

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Laboratory: 1. Introduction to digital signals sampling properties, aliasing, simple digital notch filter behaviour 2. Response of a recursive (HR) digital filter comparison to ideal unit sample and frequency response coefficient quantization effects. 3. Scaling dynamic range and noise behaviour of a recursive digital filter, observation of nonlinear finite precision effects.

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