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Learn MoreDigital Signal Processing with MATLAB Applications
Rating: 4.1 out of 54.1(107 ratings)
3,525 students
Digital Signal Processing with MATLAB Applications
Digital signal processing with MATLAB applications
Created byProf. Dr. Academic Educator
Last updated 3/2023
English
What you'll learn
- Digital Signal Processing Topics with MATLAB Applications
Explore related topics
Course content
8 sections • 43 lectures • 15h 39m total length
- Introduction3:00
In this lecture, the outline of the course is provided.
- Sampling of continuous time signals21:23
In this lecture, sampling operation on a continuous time signal is explained, and the meaning of sampling frequency is elaborated.
- Sampling operation in time domain using MATLAB16:41
In this lecture, sampling operation in time domain is explained using MATLAB programming
- Effect of Sampling Frequency is Demonstrated using MATLAB8:45
Using MATLAB we illustrate the meaning of sampling frequency
- Time domain formulas for sampling operation15:55
In this lecture, we derive some time domain formulas for the sampling operation.
- Frequency domain formulas for sampling operation17:04
In this lecture, frequency domain formulas for sampling operation are derived.
- Calculation of the Fourier transforms of continuous time signals using MATLAB14:54
Fourier transform calculation of continuous time signals are explained by MATLAB
- Calculation of the Fourier transforms of DIGITAL signals using MATLAB18:44
In this lecture, Fourier transform of DIGITAL signals will be calculated using MATLAB programming
- Drawing the graph of Fourier transform of the product signal xs(t)=xc(t) x s(t)17:56
In this lecture, we draw the graph of the Fourier transform of the product signal xs(t)=xc(t) x s(t) where xc(t) is the continuous time signal to be samples and s(t) is the impulse train
- Drawing the Fourier transform of the product signal for overlapping cases20:30
The graph of the Fourier transform of the product signal is drawn for overlapping cases
- Reconstruction of an Analog Signal from its Samples19:43
In this lecture, we will derive the mathematical expressions for the reconstruction of an analog signal from its samples.
- Analog signal reconstruction example17:54
In this lecture, reconstruction of an analog signal from its samples is illustrated by an example
- Writing a MATLAB code for the reconstruction of analog signal from its samples17:01
In this lecture, we explain how to write a MATLAB code for the reconstruction of an analog signal from its samples. We illustrate the concept with an example.
- Effect of Sampling Period on the Reconstructed Signal is shown using MATLAB19:05
In this lecture, we illustrate the effect of sampling frequency on the reconstructed signal using a MATLAB code. The MATLAB code is run using different sampling frequencies, and the reconstructed signals are compared.
- Approximation of the reconstruction filter, linear approximation12:47
In this lecture, we will explain how to approximate the reconstruction filter and obtain its linear version, then illustrate its use by an example.
- DownSampling of Digital Signals in Time Domain11:04
In this lecture, we will explain the downsampling operation performed for digital signals in time domain.
- Downsampling in time domain using MATLAB13:29
In this lecture, we explain the downsampling operation in time domain using MATLAB
- Downsampled signals in frequency domain using MATLAB25:37
In this lecture, we inspect the spectrum of the downsampled signals in MATLAB
- Fourier Transform of Downsampled Signal20:23
In this lecture, we will derive the mathematical expression for the Fourier transform of the downsampled signal.
- Verification of the Fourier Transform of Downsampled Signal15:08
In this lecture, we verify the Fourier transform of the downsampled signal mathematically.
- Drawing The Spectrum Of Downsampled Signal15:23
In this lecture, we explain how to draw the spectrum of downsampled signals by examples.
- Aliasing in Downsampling29:02
In this lecture, we explain the aliasing in downsampled signal, and derive a criteria for the downsampling factor.
- Sampling Period Interpretation in Downsampling11:32
In this lecture, we interpret the sampling period of the downsampled signal.
- Decimator Filter24:51
In this lecture, we explain decimator filter used before downsampling operation.
- Decimator/Decimation Filter in MATLAB33:58
In this lecture, we explain the decimation filter using MATLAB
- Upsampling operation in time domain21:37
In this lecture, we explain the upsampling of digital signals in time domain.
- Fourier transform of upsampled signal13:36
In this lecture, we inspect the Fourier transform of upsampled signal.
- Interpolation of digital signals30:16
In this lecture, we explain the interpolation of digital signals.
- Approximation of interpolation filter, and numerical example for interpolation31:56
In this lecture, we explain the approximated interpolation filter, and provide an example for the interpolation of a digital signal.
- Sample and hold and quantization36:13
Sample-and-old operation and quantization process are explained.
- Practical DC converter21:09
This lecture is a continuation of the previous lecture, and in this lecture we explain practical D/C converters.
- Manipulation of digital non-periodic and periodic signals.32:22
We explain time-shifting, time-scaling, and rotation operations for non-periodic and periodic digital signals.
- Manipulation of periodic digital signals20:29
We continue explaining the manipulation of periodic signals involving combined shifting and scaling operations.
- Review of signal types and transforms23:29
In this lecture, we refresh our knowledge about the Fourier transforms of the periodic and non-periodic continuous and digital signals.
- Periodic convolution and sampling of Fourier transform22:55
In this lecture, we explain the topics Periodic convolution and sampling of Fourier transform
- Discrete and Inverse Discrete Fourier Transform Calculation - 130:46
In this lecture, we show how to calculate the DFT and inverse DFT coefficients of non-periodic digital signals. We derive necessary formulas, and solve numerical examples for clear illustration.
- Discrete and Inverse Discrete Fourier Transform Calculation - 214:09
The previous lecture is continued
- Alising in Time Domain18:31
In this lecture, we explain the aliasing problem in time domain, and talk about some properties of discrete Fourier series coefficients
- Circular Convolution31:52
In this lecture, we explain how to calculate the circular convolution of two non-periodic digital signal.
- LTI Systems, Stability, Causality, Z-Transform, Laplace Transform42:58
In this lecture, we review some fundamental concepts like LTI systems, Z-transform, Laplace transform, stability, causality, etc.
- Transformation Between Continuous and Discrete Time Systems34:31
In this lecture, we explain the transformation of a continuous time system to a discrete time system.
- Practical Analog Filter Design42:35
In this lecture, we provide information about practical analog filters, and explain how to design a low-pass Butterworth analog filter. We also provide a numerical example for low-pass Butterworth analog filter design
- Digital IIR Filter Design28:42
In this lecture, we explain how to design a digital IIR lowpass filter.
Requirements
- Signals and systems would be good
Description
In this course digital signal processing topics will be explained both theoretically and using MATLAB programming. The sampling opeation will be explained both in time domain and frequency domain. Upsampling and downsampling operations will be explained in details. Reconstruction of analog signals from digital signals is another topic to be covered in this course. Discrete Fourier transform is covered in details. The design of analog and digital IIR filters is covered in this course.
Who this course is for:
- Anyone interested in digital signal processing