Digital Signal Processing (DSP) From Ground Up™ with MATLAB
4.1 (310 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
1,910 students enrolled

Digital Signal Processing (DSP) From Ground Up™ with MATLAB

Practical DSP with Matlab : FFT, Filter Design, Convolution, IIR, FIR, Hamming Window, Linear Systems, ECG processing
4.1 (310 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
1,910 students enrolled
Created by Israel Gbati
Last updated 4/2020
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Current price: $90.99 Original price: $129.99 Discount: 30% off
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This course includes
  • 5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Be able to perform convolution with matlab
  • Be able to perform Fast Fourier Transform (FFT) with matlab
  • Be able to perform Inverse Fast Fourier Transform (IFFT) with matlab
  • Be able to perform spectral analysis of ECG signals with matlab
  • Be able to design Finite Impulse Response (FIR) filters with matlab
  • Be able to design Infinite Impulse Response (IIR) filters with matlab
  • Be able to compute the Running Sum of a signal with matlab
  • Be able to compute the First Difference of a signal with matlab
  • Be able to compute the Moving Average of a signal with matlab
  • Be able to build passive Low-pass and High-pass filters
  • Be able to build Modified Sallen-Key filters
  • Be able to build Bessel, Chebyshev and Butterworth filters
  • Understand all about Linear Systems and the characteristics
  • Understand how to synthesize and decompose signals
Course content
Expand all 91 lectures 05:02:35
+ Getting Started
10 lectures 46:09
Introduction to Matrices
08:53
Matrix concatenation
02:37
Working with Complex Numbers
01:28
Array Indexing
04:53
Saving and loading variables
03:16
Plotting 2D graphs
06:46
Plotting multiple graphs
03:07
Dealing with missing data
08:12
Writing to a file
04:10
Reading from a file
02:47
+ Signal Statistics and Noise
4 lectures 12:02
Mean and Standard Deviation
04:10
Signal-to-Noise ratio
00:58
Coding : Signal statistics
04:28
+ Quantization and The Sampling Theorem
8 lectures 23:04
Quantization
02:31
Nyquist Theorem ( Sampling Theorem )
02:15
The Passive Low-Pass Filter
05:59
The Passive High-Pass Filter
02:29
The Modified Sallen-Key Filter
02:19
The Bessel, Chebyshev and Butterworth filters
03:28
Comparing the performance of the Bessel, Chebyshev and Butterworth filters
02:36
Information encoding : Time-domain and frequency-domain encoding
01:27
+ Linear Systems and Superposition
7 lectures 10:40
Signal naming conventions
01:17
System Homogeneity
01:32
System Additivity
00:33
System Shift Invariance
01:06
Synthesis and Decomposition
02:11
Impulse Decomposition
02:10
Step Decomposition
01:51
+ Convolution
12 lectures 48:48
Introduction to Convolution
01:33
The Delta Function and Impulse Response
02:13
The Convolution Kernel
07:22
The Convolution Kernel (Part II)
00:53
The Convolution Kernel (Part III)
04:01
The Output side analysis and the convolution sum equation
04:20
The Identity property of convolution
01:30
Coding : Performing convolution in matlab (Part I)
08:24
Coding : Performing convolution in matlab (Part II)
06:29
The Running Sum and First Difference
02:02
Coding : Computing the Running Sum of a signal in matlab
05:07
Coding : Computing the First Difference of signal in matlab
04:54
+ Fourier Transform
11 lectures 43:58
Introduction to Fourier Analysis
01:22
Introduction to Discrete Fourier Transform
04:50
DFT Basis Functions
03:23
Deducing the Inverse DFT
03:12
Coding : Computing the Inverse DFT of a signal
08:02
Calculating the Discrete Fourier Transform (DFT)
03:55
Coding : Computing the DFT of a signal
09:24
Symmetry between Time domain and frequency domain -Duality
00:55
Polar Notation
02:50
Introduction to Spectral Analysis
02:31
The Frequency Response
03:34
+ Complex Numbers
5 lectures 08:46
The Complex Number System
02:05
Polar Representation of Complex Numbers
01:35
Euler's Relation
01:35
Representation of Sinusoids
01:57
Representing Systems
01:34
+ Complex Fourier Transform
4 lectures 07:14
Introduction to Complex Fourier Transform
01:43
Mathematical Equivalence
01:38
The Complex DFT Equation
00:36
Comparing Real DFT and Complex DFT
03:17
+ Fast Fourier Transform (FFT)
3 lectures 19:52
An Overview of how FFT works.
08:17
Understanding the complexity of calculating DFT directly
02:35
How the Decimation -in-Time FFT Algorithm works
09:00
Requirements
  • Having basic programming skills is a plus
Description

With a programming based approach, this course is designed to give you a solid foundation in the most useful aspects of Digital Signal Processing (DSP) in an engaging and easy to follow way. The goal of this course is to present practical techniques while avoiding  obstacles of abstract mathematical theories. To achieve this goal, the DSP techniques are explained in plain language, not simply proven to be true through mathematical derivations.

Still keeping it simple, this course comes in different programming languages and hardware architectures so that students can put the techniques to practice using a programming language or hardware architecture  of their choice. This version of the course uses the MATLAB programming language.


By the end of this course you should be able to perform Convolution with matlab, perform  Discrete Fourier Transform (DFT)  with matlab, perform Inverse Discrete Fourier Transform (IDFT)  with matlab , design and develop Finite Impulse Response (FIR) filters with matlab, design and develop Infinite Impulse Response (IIR) filters  with matlab, develop Windowed-Sinc filters with matlab, build Modified Sallen-Key filters,  build Bessel, Chebyshev and Butterworth filters,  even give a lecture on DSP and so much more. Please take a look at the full course curriculum.

Some of the theory in this course is based on "The Scientist and Engineer's Guide to Digital Signal Processing" by  Steven W. Smith. You can download a free copy online.

Who this course is for:
  • Engineering Students
  • Embedded Systems Engineers
  • Embedded Systems Instructors
  • Hobbyists
  • Developers