Digital Signal Processing With Matlab

From Basics to Applications

What you'll learn

To introduce the fundamental concepts and applications of Digital Signal Processing (DSP)

To enable learners to implement and analyze DSP algorithms using MATLAB.

To provide hands-on experience in filter design, frequency analysis, and multirate processing.

Apply DSP techniques to real-world problems through hands-on MATLAB coding.

Requirements

Basic knowledge of signals and systems

Fundamentals of mathematics

Basic programming skill

Description

Welcome to Digital Signal Processing with MATLAB: From Basics to Applications – a comprehensive and practical course designed to provide you with a solid foundation in digital signal processing (DSP) using MATLAB. Whether you're an engineering student, a researcher, or an industry professional, this course offers a hands-on approach to understanding and applying DSP concepts through MATLAB coding and simulations.In this course, you will start by learning the fundamentals of DSP, including discrete-time signals, systems, and the core principles behind Fourier analysis. We’ll explore Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), and their real-world applications, allowing you to analyze and process signals in both the time and frequency domains.You’ll dive into the design and implementation of IIR and FIR filters, learn about filter realizations, and gain practical experience in multirate signal processing techniques like decimation and interpolation. Through step-by-step MATLAB examples, you will not only grasp theoretical concepts but also apply them to real-world problems, such as audio processing, biomedical signal analysis, and communications.By the end of this course, you will have the practical skills to design filters, analyze signals, and implement DSP algorithms in MATLAB. Whether you are looking to advance your academic knowledge or develop professional expertise, this course will equip you with the tools needed to apply DSP in various domains.

Overview

Section 1: DSP Fundamentals & Discrete Fourier Transform (DFT)

Lecture 1 Introduction & Applications to DSP Systems

Lecture 2 Classification of Discrete-Time Systems

Lecture 3 Discrete Fourier Transform (DFT): Definition and Computation

Lecture 4 Classification of signals &Applications of DSP

Lecture 5 Circular convolution using MATLAB

Lecture 6 Frequency Domain Representation

Section 2: Fast Fourier Transform (FFT)

Lecture 7 FFT:Advantages, Methods, and Examples

Section 3: IIR Digital Filter Design

Lecture 8 Design Procedure for Butterworth IIR Filter

Section 4: FIR Digital Filter Design

Lecture 9 window techiques

Lecture 10 FIR Filter Design

Section 5: Realization Techniques

Lecture 11 Realization Techniques-Z Transform

Lecture 12 Realization of Discrete-Time Systems-1

Lecture 13 Realization of Discrete-Time Systems-2

Section 6: Multirate Processing

Lecture 14 Multi Rate signal processing :An Overview of Concepts and Applications

Section 7: DSP Lab Experiments & capstone project

Lecture 15 Introduction to Matlab and operations on matrices

Lecture 16 Classification of Discrete systems using MATLAB

Lecture 17 Linear convolution using MATLAB

Lecture 18 Circular convolution using MATLAB

Lecture 19 Design of IIR Filters using Impulse invariant method

This course is ideal for: Undergraduate and postgraduate engineering students studying Electrical, Electronics, or Communication Engineering, who want a strong foundation in DSP concepts using MATLAB. Academic project students or researchers looking to apply DSP techniques in practical areas like speech, biomedical, or communication systems. Industry professionals in embedded systems, signal processing, or telecommunications seeking to refresh or strengthen their DSP skills through hands-on MATLAB simulations. Anyone with an interest in signal processing who wants to learn how to implement real-world DSP applications using MATLAB — even if you're new to MATLAB.