Digital Signal Processing
Course Objective:
Digital Signal Processing is one of the most powerful subject that will the base or foundation of science and engineering in the twenty-first century. Revolutionary changes have already been made in a broad range of fields: communications, medical imaging, radar & sonar, high fidelity music reproduction, and oil prospecting, to name just a few. Each of these areas has developed a deep DSP technology, with its own algorithms, mathematics, and specialized techniques. This combination of breath and depth makes it impossible for any one individual to master all of the DSP technology that has been developed. DSP education involves two tasks: learning general concepts that apply to the field as a whole, and learning specialized techniques for your particular area of interest.
The reason to explore the domain of interest and field of engineer to motivate to the mathematician and the engineer towards Digital Signal Processing (DSP) in the following fields:
Sound applications –Compression, enhancement, special effects, synthesis, recognition, echo cancellation, Cell Phones, MP3 Players, Movies, Dictation, Text-to-speech,…
Communication- Modulation, coding, detection, equalization, echo cancellation, Cell Phones, dial-up modem, DSL modem, Satellite Receiver,…
Automotive–ABS, GPS, Active Noise Cancellation, Cruise Control, Parking,…
Medical–Magnetic Resonance, Tomography, Electrocardiogram,…
Military–Radar, Sonar, Space photographs, remote sensing,…
Image and Video Applications–DVD, JPEG, Movie special effects, video conferencing,…
Mechanical–Motor control, process control, oil and mineral prospecting,…
Course Syllabus:
Course Lecture:
Module 1_Lec1 to Lec 5- Discreat-time signal: Concept of discrete-time signal, basic idea of sampling and reconstruction of signal, sampling theorem, sequences,-periodic, energy, power, unit-sample, unit step, unit ramp & complex exponentials, arithmetic operations on sequences.
Module 1_Lec 6 to Lec 10- LTI systems: Definition, representation, impulse response, derivation for the output sequence, concept of convolution, graphical, analytical and overlap-add methods to compute convolution supported with examples and exercise, properties of convolution, interconnection of LTI systems with physical interpretations, stability and causality conditions, recursive and non recursive systems.
Module 2_Lec 11 to Lec 17- Z- Transforms: Definition, mapping between s-plane & z-plane, unit circle, convergence and ROC, properties of Z-transform, Z-transform on sequences with examples & exercises, characteristic families of signals along with ROC, convolution, correlation and multiplication using Z- transform, initial value theorem, Perseval’s relation, inverse Z- transform by contour integration, power series & partial-fraction expansions with examples and exercises.
Module 2_Lec 18 to Lec 24-Discrete Fourier Transform: Concept and relations for DFT/IDFT, Relation between DTFT & DFT. Twiddle factors and their properties, computational burden on direct DFT, DFT/DFT as linear transformation, DFT/IDFT matrices, computation of DFT/IDFT by matrix method, multiplication of DFTs, circulation convolution, computation of circular convolution by graphical, DFT/IDFT and matrix methods, linear filtering using DFT, aliasing error, filtering of long data sequences Overlap-Save and Overlap-Add methods with examples and exercises.
Module 2_Lec 25 to Lec 30- Fast Fourier Transforms:Radix-2 algorithm, decimation-in-time, decimation-in-frequency algorithm, signal flow graph, Butterflies, computations in one place, bit reversal, examples for DIT & DIF FFT Butterfly computations and exercises.
Module 3_Lec 31 to Lec 35- Filter design:Basic concepts of IIR and FIR filters, difference equations, design of Butterworth IIR analog filter using impulse invariant and bilinear transform, design of linear phase FIR filters no. of taps, rectangular, Hamming and Blackman windows. Effect of quantization.
Module 4_Lec 36 to Lec 40- Digital Signal Processor :Elementary idea about the architecture and important instruction sets of TMS320C 5416/6713 processor, writing of small programs in assembly Language. FPGA: Architecture, different sub-systems, design flow for DSP system design, mapping of DSP alrorithms onto FPGA.
Course Assessment:
1] Homework and Assignments [20%]:
2] Term Paper/ Mini Projects [30%]:
3] Midterm and Class Test [50%]:
Recommended Books/References:
1] Digital Signal Processing in Communication Systems by Marvin E. Frerking.
2] Discrete-Time Signal Processing by A. V. Oppenheim and R. W. Schafer.
3]Digital Signal Processing: Principles, Algorithms, and Applications by J. G. Proakis and D. G. Manolakis.
For high-level reference books written for those who are already DSP experts. Please refer
1] Multirate Digital Signal Processing by R. E. Crochiere and L. R. Rabiner.
Here are some classic name of DSP books which have been widely used--but are now out of print
1] Theory and Application of Digital Signal Processing by Rabiner and Gold. A comprehensive, industrial-strength DSP reference book.
2] Digital Signal Processing by Alan V. Oppenheim and Ronald W. Schafer. Another industrial-strength reference. (Replaced by the authors' Disrete-Time Signal Processing)
3] Digital Signal Processing by William D. Stanley. A very readable book; has a strong treatment of IIR filters.
All ECE1 students are requested to please come to the GF 02 before attend the DSP Lab which is scheduled in Arabinda Bhaban.
Other resources:
Lecture "Pattern Recognition and Machine Learning"
Lecture notes of Advance Digital Signal Processing by Gerhard Schmidt
Continuous time trigonometric representation of of CT periodic signals – Tutorials
Reference ebooks fo Sophocles J. Orfanidis:
Lab resource:
1. Digital Signal Processing Laboratory
2.