Digital Signal Processing With Matlab (2025)
Digital Signal Processing With Matlab (2025)
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Published 5/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.59 GB | Duration: 4h 51m
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.
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