Course Title: Digital Filter Design
Type of Course: Optional, Theory
Offered to: EEE
Pre-requisite Course(s): None
Application of digital filters, analog filters, linear phase FIR filters, optimal filter design, Remez exchange algorithm, multiband filters, approximately linear phase IIR filter, all pass filter, design of IIR filter using optimization methods: Newton’s method, Quasi-Newton algorithms, Minimax algorithms, improved Minimax algorithms, filter design in time-frequency domain, design of special filters: Hilbert transformer, narrowband filter, fractional delay filter, Wiener filter, filter design using Kalman filter/parallel Kalman filter, Wavelet filter.
The major goal of the course is to provide a solid foundation for the students to study advanced topics in designing digital filters including the recursive, non-recursive and special type of filters. With the exercise of mathematical formulations for given specifications of practical problems, the students will be able to design and evaluate the performance of digital filters.
N/A
Upon completion of this course, the successful student will be able to-
| COs | CO Statements | Mapping with POs | Learning Domain (Taxonomy Level) |
|---|---|---|---|
| CO1 | Recall the concept of sampling and frequency, and the fundamentals of digital signal processing to solve the engineering problems of digital filter design. | PO(a) | Cognitive (Comprehension) |
| CO2 | Apply the theory of Z-transform and Fourier transform to formulate the parameters of the filter as per design specifications. | PO(a), PO(b) | Cognitive (Comprehension + Analysis + Application) |
| CO3 | Understand the methodology of optimization technique and employ the idea in obtaining the parameters of the digital filters. | PO(a), PO(b) | Cognitive (Comprehension + Analysis + Application) |
| CO4 | Identify real-life applications of digital filter and design efficient engineering solution. | PO(a), PO(b), PO(c) | Cognitive (Comprehension + Analysis + Design) |
Cognitive Domain Taxonomy Levels: C1 – Knowledge, C2 – Comprehension, C3 – Application, C4 – Analysis, C5 – Synthesis, C6 – Evaluation, Affective Domain Taxonomy Levels: A1: Receive; A2: Respond; A3: Value (demonstrate); A4: Organize; A5: Characterize; Psychomotor Domain Taxonomy Levels: P1: Perception; P2: Set; P3: Guided Response; P4: Mechanism; P5: Complex Overt Response; P6: Adaptation; P7: Organization
Program Outcomes (PO): PO(a) Engineering Knowledge, PO(b) Problem Analysis, PO(c) Design/development Solution, PO(d) Investigation,
PO(e) Modern tool usage, PO(f) The Engineer and Society, PO(g) Environment and sustainability, PO(h) Ethics, PO(i) Individual work and team work,
PO(j). Communication, PO(k) Project management and finance, PO(l) Life-long Learning
* For details of program outcome (PO) statements, please see the departmental website or course curriculum
| K1 | K2 | K3 | K4 | K5 | K6 | K7 | K8 | P1 | P2 | P3 | P4 | P5 | P6 | P7 | A1 | A2 | A3 | A4 | A5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Topics (According to syllabus in Academic Calendar, 2021) | Lectures (Weeks) | Mapping with COs |
|---|---|---|
| Introduction: Preliminaries of finite word length of digital filters, review of Z-transforms and discrete Fourier transform, application of digital filters | 1-3 (1) |
CO1 |
| Analog Filters: Introductory concepts, approximations by Butterworth filter, Chebyshev filter, elliptic filter, and Bessel filter | 4-6 (2) |
CO1 |
| Recursive Filters: IIR filter, Realizability constraint, invariant-impulse- response method, matched z-transformation, bilinear transformation. Filter design procedure, constant group delay, amplitude equalization | 7-12 (3-4) |
CO2 |
| Non-recursive Filters: FIR filter, Properties of non-recursive filters, window functions, numerical analysis, comparisons between recursive and non-recursive filters | 13-18 (5-6) |
CO2 |
| Finite Length Digital Filters: Number representation, quantization, signal scaling, error-spectrum shaping | 19-24 (7-8) |
CO2 |
| Recursive Filters and Optimization: Problem formulation, quasi-Newton algorithm, minimax algorithm, designing recursive delay equalizers, real-life appltcations | 25-30 (9-10) |
CO2 CO3 CO4 |
| Non-recursive Filters and Optimization: Problem formulation, Remez exchange algorithm, gradient information, search methods, digital differentiators, multiband filters, real-life appltcations | 31-36 (11-12) |
CO2 CO3 CO4 |
| Special Filters:, Hilbert transform, narrow band filter, Wiener filter, Kalman Filter, Wavelet filters | 37-39 (13) |
CO2 CO3 |
Class Attendance and Participation
Class participation and attendance will be recorded in every class. Participation and attendance for the students may be considered in case the student could not attend the class due to a valid reason (power failure, internet problem, device problem, health problem, etc.). The student has to inform the teacher over email in case of such occurrences. A maximum of three (03) such missed classes can be considered for this course
Quiz, Assignment, Viva and Presentation
Four nos. of tests (Quiz, Assignment, Viva and Presentation) will be taken and best 3 nos. will be counted.
Final Examination
A comprehensive term final examination will be held at the end of the Term following the guideline of Academic Council.
Class Participation 10%
Continuous Assessment 20%
Final Examination 70%
Total 100%
Andreas Antoniou, “Digital Filters: Analysis Design, and Applications,” Second Edition, McGraw-Hill, 2008
Dietrich Schlichthärle, “Digital Filters: Basics and Design,” Springer Nature, 2011
Takao Hinamoto, Wu-Sheng Lu, “Digital Filter Design and Realization,” River Publishers, 2017