Digital Signal Processing

Latest uploads: 

 6.  DSP_Tutorial_05 (Unit-III : Design of IIR Filters : Impulse Invariance method)
 5.  DSP_Tutorial_04 (Overlap Add , Overlap Save (method 1) examples)
  4.   DSP_Tutorial_03 (Only for practise, not for submission)
 3.  8_point_FFT (step-by-step tutorial)
 2.  DSP_Tutorial_02  (Only for practise, not for submission)
 1.  DSP LAB MANUAL

Text Books :                                      3ECEA Time Table

1. Digital Signal Processing, Principles, Algorithms, and Applications: John G. Proakis, Dimitris G. Manolakis, Pearson Education / PHI, 2007.
2. Discrete Time Signal Processing - AV Oppenheim and R. Schaffer, PHI, 2009.
3. Fundamentals of Digital Signal Processing - Loney Ludeman, Wiley,2009.

Reference Books

1. Digital Signal Processing - Fundamentals and Applications - Li Tan, Elsevier, 2008 
2. Fundamentals of Digital Signal Processing using MATLAB - Robert. J. Schilling, Sandra L. Harris, Thomson, 2007. 
3. Digital Signal Processing - S. Salivahanan, A. Vallavaraj, C. Gnanapriya, TMH, 2009. 
4. Discrete Systems and Digital Signal Processing with MATLAB - S. EL Ali, CRC Press, 2009. 
5. Digital Signal Processing - A Practical approach , Emmanuel Ifeachor and Barrie W. Jervis, 2nd Edition, Pearson Education, 2009
6. Digital Signal Processing - Nagoor Kani, TMG, 2012
7. Matlab for Engineers , Holly Moore, Third Edition

Announcements, Assignments, Problems, Short Notes and other miscellaneous stuff can be accessed by clicking on the "DSP Folder" link below.
DSP FOLDER

Course Objectives  :

This course is an essential course that provides design techniques for processing all types of signals in various fields. The main objectives are :

1. To provide background and fundamental material for the analysis and processing of digital signals and systems.
2. To familiarise the relationships between continuous-time and discrete-time signals and systems.
3. To study fundamentals of time, frequency and z-plane analysis and to discuss the inter-relationships of these analytic method.
4. To study the designs and structures of digital (IIR and FIR) filters from analysis to synthesis for a given set of specifications.
5. The impetus is to introduce a few real-world signal processing applications.
6. To acquaint in FFT algorithms, Multi-rate signal processing techniques and finite word length effects.

This course will also help the students to

• Provide a deeper understanding of the latest developments in the DSP research area.
• Present a comprehensive introduction to important emerging DSP technologies.

Course Specific Objectives :

Upon completion of this course, student will be able to :

1. Apply digital signal processing fundamentals. 
2. Understand the processes of analog-to-digital and digital-to-analog conversion. 
3. Master the representation of discrete-time signals in the frequency domain, using z-transform, discrete Fourier transform (DFT), and cosine transform. 
4. Understand the implementation of the DFT in terms of the FFT, as well as some of its applications (computation of convolution sums, spectral analysis). 
5. Learn the basic forms of FIR and IIR filters, and how to design filters with desired frequency responses. 
6. Appreciate relationships between first order low pass, and high pass filters, and between second-order Peaking and Notching filters. Design digital filters using Matlab. 
7. Use appropriate windows to diminish the effect of leakage. 
8. Demonstrate the effect of the time window length on the achievable spectral resolution. 
9. Learn the design procedures for filter bank. 
10. Become aware of some applications of digital signal processing. 

Topics covered:

1. Review of analog signals, discrete time signals, linear shift invariant systems, Impulse response,      linear convolution, and Matrix formulations of a linear convolution.
2. The DTFT, The linear convolution theorem, DTFT of a rectangular window. Relation with the CTFT, The sampling theorem, Spectra of sampled signals, The Nyquist theorem. Aliasing, Signal reconstruction. Sample rate, decimation & interpolation. Quantization. Oversampling and noise shaping. A/D and D/A  Converters. Quantization, finite word length effects.
3. DFT Properties, DFT of the rectangular window, Zero padding, DFT examples, Sampling of periodic signals and the DFT. The DFT matrix, Frequency resolution and windowing, Physical vs. computational resolution.
4. Factorizations of the DFT matrix. FFT algorithms: Decimation in frequency FFT. The FFT vs. the DFT. Circular convolution, The Circular convolution theorem, fast block convolution; Discrete Fourier and Cosine transforms;
5. Z- Transform, Properties, Region of convergence, Causality and stability, Relation to the DTFT. The pole-zero pattern and its relation with the filter magnitude frequency response, Partial fraction expansion, Inverse Z- transform, Transform pairs.
6. Summary of equivalent description of digital filters (system function H(z), frequency response H(w), I/O difference equation, Pole zero pattern, Impulse response, I/O Convolution Equation). Difference equations and IIR filters.
7. Develop the fundamentals of digital filter design techniques for Finite Impulse Response (FIR Fourier technique based digital filters design methods) and Develop Infinite Impulse Response filter types (IIR-Bilinear transformation, First order low pass, and high pass filters, second-order Peaking and Notching filters, higher order filter, including Butterworth and Chebyshev filters). Comparisons between FIR and IIR filters will be presented. MATLAB design examples will be also presented.
8. Multirate processing fundamentals of decimation and interpolation will be developed. Methods for optimizing processing throughput requirements via multirate designs will be developed.
9. Analog-to-Digital conversion errors will be studied. Quantization effects of finite arithmetic for   common digital signal processing algorithms including digital filters and FFTs will be presented. Methods of calculating the noise at the digital system output due to arithmetic effects will be developed.
10. Several algorithms and associated applications need to be discussed based upon classical and recent papers/research