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Digital Signal Processing (DSP) From Ground Up™ in Python

Digital Signal Processing (DSP) From Ground Up™ in Python

Loại khoá học: Engineering

Practical DSP in Python : Over 70 examples, FFT,Filter Design, IIR,FIR, Window Filters,Convolution,Linear Systems etc

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50.000 VND
1.099.000 VND
Đầy Đủ Bài Giảng
Học Online Tiện Lợi
Kích Hoạt Nhanh 2-5 Phút
Thanh toán tự động
Được phép tải xuống

Tổng quan

Nội dung khoá học

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Mô tả

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 Python programming language.


By the end of this course you should be able develop the Convolution Kernel algorithm in python,  develop 17 different  types  of window  filters in python, develop the Discrete Fourier Transform (DFT) algorithm in python, develop the Inverse Discrete Fourier Transform (IDFT) algorithm in pyhton, design and develop Finite Impulse Response (FIR) filters in python, design and develop Infinite Impulse Response (IIR) filters in python, develop Type I Chebyshev filters in python, develop Type II Chebyshev filters in python, perform spectral analysis on ECG signals in python,  develop Butterworth filters in python, develop Match filters in python,simulate Linear Time Invariant (LTI) Systems in python, even give a lecture on DSP and so much more. Please take a look at the full course curriculum.

Bạn sẽ học được gì

Develop the Convolution Kernel algorithm in Python

Design and develop 17 different window filters in Python

Develop the Discrete Fourier Transform (DFT) algorithm in Python

Design and develop Type I Chebyshev filters in Python

Design and develop Type II Chebyshev filters in Python

Develop the Inverse Discrete Fourier Transform (IDFT) algorithm in Pyhton

Develop the Fast Fourier Transform (FFT) algorithm in Python

Perform spectral analysis on ECG signals in Python

Design and develop Windowed-Sinc filters in Python

Design and develop Finite Impulse Response (FIR) filters in Python

Design and develop Infinite Impulse Response (IIR) filters in Python

Develop the First Difference algorithm in Python

Develop the Running Sum algorithm in Python

Develop the Moving Average filter algorithm in Python

Develop the Recursive Moving Average filter algorithm in Python

Design and develop Butterworth filters in Python

Design and develop Match filters in Python

Design and develop Bessel filters in Python

Simulate Linear Time Invariant (LTI) Systems in Python

Perform linear and cubic interpolation in Python

Yêu cầu

  • You will need just a good working computer for this course

Nội dung khoá học

20 sections

Set Up

5 lectures
Downloading Python
01:49
Installing Python
01:59
Using IDLE
02:52
Installing Python packages
03:37
Testing the packages
07:16

Python Essentials

10 lectures
Printing statements
06:06
Variables
07:19
Lists
05:17
Operators
12:23
Conditions
08:14
For Loops
07:28
While Loops
05:26
Functions
07:44
Dictionaries
10:17
Classes and Objects
12:23

Signal Statistics and Noise

11 lectures
Signal Statistics and Noise
04:07
Coding : Plotting signals with pyplot
07:35
Coding : Importing signals and dealing with subplots
12:31
Coding : Generating signals
12:07
Mean and Standard Deviation
04:06
Coding : Computing the Signal Mean
04:42
Coding : Developing the Signal Mean algorithm
05:33
Coding : Computing the Signal Variance
01:57
Coding : Developing the Signal Variance algorithm
07:27
Coding : Computing the Standard Deviation
02:19
Coding : Developing the Signal Standard Deviation algorithm
03:06

Quantization and The Sampling Theorem

5 lectures
Nyquist Theorem ( Sampling Theorem )
09:24
The Passive Low-Pass Filter
07:30
The Passive High-Pass Filter
04:48
The Active Filter
05:49
The Bessel, Chebyshev and Butterworth filters
06:44

Linear Systems and Superposition

3 lectures
Introduction to Linear Systems
04:47
Understanding Superposition
05:00
Impulse and Step Decomposition
04:31

Convolution

16 lectures
Introduction to Convolution
03:22
The Convolution Operation
06:44
Examinging the Output of Convolution
04:45
The Convolution Sum Equation
02:05
A Closer look at the Delta function
05:41
Coding : Examining the signals
07:19
Coding : Computing the convolution of two signals
07:07
Coding : Developing the Convolution algorithm
21:11
Coding : Computing the De-convolution of two signals
06:19
Coding : Correlation
07:17
The Identity property of convolution
01:30
The Running Sum and First Difference
01:55
Coding : Computing the running sum of a signal
08:04
Coding : Developing the Running Sum algorithm
06:52
Coding : Computing the First Difference of a signal
03:12
Coding : Developing the First Difference algorithm
06:27

Fourier Transform

11 lectures
Introduction to Fourier Analysis
05:29
The DFT Engine
04:11
Understanding Forward and Inverse DFT
04:32
Coding : Developing the Discrete Fourier Transform (DFT) algorithm
15:53
Coding : Developing the DFT magnitude algorithm
10:03
Coding : Developing the Inverse Discrete Fourier Transform (IDFT) algorithm
20:35
Coding : Computing the IDFT of an ECG signal
05:25
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
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
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)

4 lectures
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
Coding : Computing the FFT of a signal
11:51

Digital Filter Design

10 lectures
Introduction to Digital Filters
03:14
The Filter Kernel
01:49
The Impulse,Step and Frequency response
01:16
Understanding the Logarithmic scale and decibels
02:59
Information representations of a signal
03:57
Time domain parameters
04:20
Frequency domain parameters
Processing..
Designing digital filters using the spectral inversion method
04:36
Designing digital filters using the spectral reversal method
02:50
Classification of digital filters
01:56

Designing Finite Impulse Response (FIR) Filters

7 lectures
The Moving Average Filter
04:11
The Multiple Pass Moving Average Filter
02:20
The Recursive Moving Average Filter
04:33
Coding : Smoothing signals with the median filter
07:19
Coding : FIR filter application project (Part I)
07:59
Coding : FIR filter application project (Part II)
12:09
Coding : FIR filter application project (Part III)
08:18

Designing Infinite Impulse Response (IIR) Filters

15 lectures
Introduction to Recursive Filters
00:46
The Recursion Equation
01:50
Coding : Computing the frequency response of a filter
05:14
Coding : Computing the frequency response of a Type I Chebyshev Bandpass Filter
05:01
Coding : Creating a Butterworth lowpass filter
05:21
Coding : Creating a Type I Chebyshev lowpass filter
06:30
Coding : Creating a Type II Chebyshev lowpass filter
04:15
Coding : Creating an Elliptic lowpass filter
05:46
Coding : Creating a Bessel lowpass filter
06:09
Coding : IIR filter application project -Butterworth filter (Part I)
07:13
Coding : IIR filter application project -Butterworth filter (Part II)
10:53
Coding : IIR filter application project -Butterworth filter (Part III)
06:38
Coding : Designing an FIR filter with a Kaiser Window (Part III)
04:42
The Single-Pole Recursive Filter
02:52
Digital Chebyshev Filters
01:57

Designing Windowed Filters

17 lectures
Introduction to Windowed-Sinc Filters
00:47
The Sinc Function and the Truncated Sinc Filter
03:15
The Blackman window
01:00
The Hamming and Blackman window equations
02:34
Designing the Windowed Sinc filter
02:34
Coding : Designing an FIR filter with a Kaiser Window (Part I)
12:15
Coding : Designing an FIR filter with a Kaiser Window (Part II)
09:56
Coding : Generating windows
08:27
Coding : Creating the Barlett-Hann Window
05:27
Coding : Creating the Barlette Window
01:14
Coding : Creating the Blackman Window
01:10
Coding : Creating the Blackman-Harris Window
01:29
Creating Bohman,Boxcar, Chebyshev, Cosine ,Flattop and Gaussian Windows
06:27
Coding : Creating the Hamming and Hanning Windows
01:42
Coding : Creating the Kaiser Window
01:33
Coding : Creating the Nuttall and Parzen Windows
02:09
Coding : Creating the Slepian and the Triangular Window
02:55

Custom Filters

5 lectures
Coding : Experimenting with the Forward-Backward filter
11:47
Coding : De-trending a signal
06:54
Coding : Comparing the performance of different Scipy filters (Part I)
05:28
Coding : Comparing the performance of different Scipy filters (Part II)
08:05
Coding : Computing the frequency response of a Remez filter
07:02

Designing Match Filters

1 lectures
Coding : Building a match filter with cross-correlation
16:22

FFT Convolution

2 lectures
Understanding how the Overlap-Add method works
04:09
Understanding how FFT-Convolution works
04:04

Representing Linear Time Invariant (LTI) )Systems in Python

5 lectures
Coding : Creating a Transfer Function
06:11
Coding : ZerosPolesGain
04:53
Coding : Frequency response of a LTI
05:44
Coding : Computing the bode plot of a LTI system
04:16
Coding : Computing the impulse response of a LTI system
03:51

Interpolation

3 lectures
Coding : Linear and cubic interpolation
07:38
Coding : Working with splines
10:30
Coding : Comparing Rbf with UnivariateSpline
10:32

Waveform Generation

2 lectures
Coding : Generating a gausspulse
05:34
Coding : Generating square waves and pulse-width modulated sine waves
08:07

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