Digital Signal Processing
Course Code: EEE 323
Credit Hour: 3
Course Group: Core Courses
Introduction to Digital Signal Processing (DSP): Digital signals and systems: Operations in digital signal processing, the scope of DSP, analog to digital conversion, frequency Domain Effects of Sampling: Periodic repetitions in frequency domain due to sampling in time domain, recovery of continuous-time signal from its samples (reconstruction), role of antialiasing and reconstruction filters, examples of aliased signals (show how waveform is distorted), impulse response, finite impulse response (FIR) and infinite impulse response (IIR) of discrete-time systems, difference equation.
Discrete Transformations: Discrete Fourier series, the Discrete-Time Fourier Transform, discrete Fourier transform (DFT) and fast Fourier transform (FFT): Forward and inverse transforms; coefficient ordering; time and frequency resolution; periodic extension, zero padding and modulo-M reduction; properties of the DFT, circular convolution; Cooley- Tukey decomposition, recursive application, radix-2 FFTs , time and frequency decimation, computational complexity.
Z-Transforms: Basic Theory: background idea behind the z-transform (solution to LTI discrete-time diff. eq.), calculation of z-transform and its inverse (briefly), regions of convergence, Properties of z-transforms: role in solution of discrete-time LTI systems, convolution property and graphical interpretation of the convolution operation, z-transforms of cascaded systems, stability and causality, Realization and frequency Response: Frequency response (Magnitude and Phase), representation of LTI systems with rational polynomials, block-form implementations of a rational polynomial transfer function.
Digital Filters: FIR filters- linear phase filters, specifications, design using window, optimal and frequency sampling methods; IIR filters- specifications, design using impulse invariant, bi-linear z-transformation, least-square methods, linear phase, Butterworth, Chebychev, Inverse Chebychev, Bessel and elliptic filters, finite precision effects in implementing digital filters.
Implementing Digital Filters: Block-diagram representations; direct forms; cascade forms, first and second-order factors; parallel forms; feedback loops transposed forms; linear-phase
FIR structures.
Wavelets: Short time Fourier transform; fundamentals of wavelets, wavelet transform (continuous and discrete), time - frequency density and orthogonal bases.
Reference Books:
- John G. Proakis, Dimitris Manolakis: Digital Signal Processing: Principles, Algorithms and Applications
- B.P. Lathi: Signal Processing and Linear System
- Simon Haykin, Barry van Veen: Signals and Systems
- Vinay K. Ingle: Digital Signal Processing Using MATLAB
- S K Mitra: Digital Signal Processing
- Salivahanan: Digital Signal Processing