Course Name: Digital Signal Processing Course Code: EE 605A Credit: 3

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Course Name: Digital Signal Processing Course Code: EE 605A Credit: 3 Prerequisites: Sl. No. Subject Description Level of Study 01 Mathematics Fourier Transform, Laplace Transform 1 st Sem, 2 nd Sem 02 Electric Circuit Theory Laplace transforms, Continuous & Discrete, Fixed & Time varying 3 rd Sem Course Objective: To make students familiar with the most important methods in DSP, including digital filter design, transform-domain processing and importance of Signal Processors. To make students aware about the meaning and implications of the properties of systems and signals. Course Outcomes: At the end of the course, a student will be able to: 1. Use concepts of trigonometry, complex algebra, Fourier transform, z-transform to analyze the operations on signals and acquire knowledge about Systems 2. Select proper tools for analog-to-digital and digital-to-analog conversion. Also select proper tools for time domain and frequency domain implementation. 3. Design, implementation, analysis and comparison of digital filters for processing of discrete time signals 4. Integrate computer-based tools for engineering applications 5. Employ signal processing strategies at multidisciplinary team activities. 6. Assess the techniques, skills, and modern engineering tools necessary for analysis of different electrical signals and filtering out noise signals in engineering practice. Also develop creative and innovative designs that achieve desired performance criteria within specified objectives and constraints, understand the need for lifelong learning and continuing professional education

CO- PO mapping: CO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 1 1 2 1 2 2 - - 2 2 2 - - 2 2 1 1 2 2 1 1 2 2 2 - - 3 2 1 1 1 - - 1 2 2 1 - - 4 1 1 1 1 1 1-1 1 1-1 5 1 2 3 2 2 2 1 2 1 1 1 1 6 2 2 2 1 - - - 1 1 1 1 3 * Enter correlation levels 1, 2 or 3 as defined below: 1: Slight (Low) 2: Moderate (Medium)3: Substantial (High) and It there is no correlation, put -

Syllabus Indicating CO: Module No. 1 2 3 4 Content Discrete-time signals: 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. 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. Discrete Time Fourier Transform(DTFT): Concept of frequency in discrete and continuous domain and their relationship (radian and radian/sec), freq. response in the discrete domain. Discrete system's response to sinusoidal/complex inputs (DTFT), Representation of LTI systems in complex frequency domain. 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. 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. 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. 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. 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. Relevant CO s CO1 CO1, CO4, CO5 CO3, CO6 CO4, CO6

Gaps in Syllabus: Sl. No. Gap Action taken Relevance to POs 1 Wavelet Transform: This can provide the frequency of the signals and the time associated to those frequencies, making it very convenient for its application in numerous fields.. Topics covered: Basic principle, Bi-orthogonal wavelet, Daubechies, Haar, LeGall,Orthogonal Wavelet, scaling Funtion. The various topics are addressed by lecture classes and by solving numerical problems. PO 1, PO 2 2 Various Window Function : This topic is very much important for Filter design, but missing in the syllabus. Topics covered: Bartlett, Blackman, Dolph- Chebyshev, Hann, Kaiser Window. Additional lecture classes are organized to cover the topics. Research literatures are provided for Filter design techniques. PO 1, PO 2, PO 5 3 Short Time fourier Transform :.This topic use for signal analysis for the particular system. Topics covered: Basic principle, Sampling in time and frequency dimention, Computation using MATLAB. Lectures classes and practical are taken to that topic. Also some research papers are provided to the students. PO 1, PO 2, PO 3, PO 5 4 Chebyshev Filter: This is another type of filter very important but not covered in the syllabus. Topics covered: Basic principle, design of chebyshev filter, The various numerical are solved in classes. PO 1

Lecture Plan: Sl. No. Date Topics Remarks 1 Discrete-time signals: Concept of discrete-time signal, basic idea of sampling and reconstruction of signal, sampling theorem 2& 3 Sequences, periodic, energy, power, unit-sample, unit step, unit ramp 4 Complex exponentials, arithmetic operations on sequences. 5 LTI systems: Definition, representation, impulse response, derivation for the output sequence 6 & 7 Concept of convolution, graphical, analytical and overlap-add methods to compute convolution supported with examples and exercise 8 Properties of convolution 9 Interconnection of LTI systems with physical interpretations, 10 Stability and causality conditions, recursive and non recursive systems. 11 Concept of frequency in discrete and continuous domain and their relationship (radian and radian/sec), 12 Freq. response in the discrete domain. 13 Discrete system's response to sinusoidal/complex inputs (DTFT), Representation of LTI systems in complex frequency domain. 14 Z- Transforms: Definition, mapping between s-plane & z-plane, unit circle, convergence and ROC 15 Properties of Z-transform, Z-transform on sequences with examples & exercises 16 Characteristic families of signals along with ROC, convolution, correlation and multiplication using Z- transform 17 & 18 Initial value theorem, Perseval s relation, inverse Z-transform by contour integration, power series & partial-fraction expansions with examples and exercises. 19 Discrete Fourier Transform: Concept and relations for DFT/IDFT, Relation between DTFT & DFT. 20 Twiddle factors and their properties, computational burden on direct DFT, DFT/DFT as linear transformation, 21 DFT/IDFT matrices, computation of DFT/IDFT by matrix method, multiplication of DFTs, circulation convolution, 22 Computation of circular convolution by graphical, DFT/IDFT and matrix methods 23 Linear filtering using DFT, aliasing error, filtering of long data sequences-overlap-save and Overlap-Add methods with examples and exercises. 24 Fast Fourier Transforms: Radix-2 algorithm, decimation-in-time, decimation-infrequency algorithm, 25 Signal flow graph, Butterflies, computations in one place, bit reversal, 26 Examples for DIT & DIF FFT Butterfly computations

27 & 28 Filter design: Basic concepts of IIR and FIR filters, difference equations, 29 & 30 Design of Butterworth IIR analog filter using impulse invariant and bilinear transform 31 & 32 Design of linear phase FIR filters no. of taps, rectangular, Hamming and Blackman windows. 33 Effect of quantization. 34 Digital Signal Processor: Elementary idea about the architecture 35 & 36 Important instruction sets of TMS320C 5416/6713 processor, 37 Writing of small programs in assembly Language. 38 & 39 FPGA: Architecture, different sub-systems, 40 & 41 design flow for DSP system design, mapping of DSP alrorithms onto FPGA. Recommended Books: 1. Digital Signal Processing-A computer based approach, S. Mitra, TMH 2. Digital Signal Processing: Principles, Algorithms & Application, J.C. Proakis & M.G. Manslakis, PHI 3. Fundamental of Digital Signal Processing using MATLAB, Robert J. Schilling, S.L. Harris, Cengage Learning. 4. Digital Signal Processing-implementation using DSP microprocessors with examples from TMS320C54XX, Avtar Singh & S. Srinivasan, Cengage Leasrning