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

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Israel Gbati,BHM Engineering Academy

13:04:08

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01 - Set Up

001 Downloading Python.mp4

01:49

002 Installing Python.mp4

01:59

003 Using IDLE.mp4

02:52

004 Installing Python packages.mp4

03:37

005 Testing the packages.mp4

07:17

02 - Python Essentials

001 0-Hello.zip

001 Printing statements.mp4

06:06

002 1-Variable.zip

002 Variables.mp4

07:19

003 2-lists.zip

003 Lists.mp4

05:17

004 3-operators.zip

004 Operators.mp4

12:23

005 4-Conditions-loops.zip

005 Conditions.mp4

08:15

006 5-loops.zip

006 For Loops.mp4

07:28

007 5-loops.zip

007 While Loops.mp4

05:26

008 6-Function.zip

008 Functions.mp4

07:44

009 8-Dictionary.zip

009 Dictionaries.mp4

10:17

010 7-Classes.zip

010 Classes and Objects.mp4

12:23

03 - Signal Statistics and Noise

001 Signal Statistics and Noise.mp4

04:07

002 9-matplotlib.zip

002 Coding Plotting signals with pyplot.mp4

07:35

003 Coding Importing signals and dealing with subplots.mp4

12:31

003 mysignals.zip

004 11-signal-generation.zip

004 Coding Generating signals.mp4

12:07

005 Mean and Standard Deviation.mp4

04:06

006 1-Mean-v1.zip

006 Coding Computing the Signal Mean.mp4

04:42

007 1-Mean-v2.zip

007 Coding Developing the Signal Mean algorithm.mp4

05:33

008 2-Variance-v1.zip

008 Coding Computing the Signal Variance.mp4

01:57

009 2-Variance-v2.zip

009 Coding Developing the Signal Variance algorithm.mp4

07:27

010 3-Standard-Deviation-v1.zip

010 Coding Computing the Standard Deviation.mp4

02:19

011 3-Standard-Deviation-v2.zip

011 Coding Developing the Signal Standard Deviation algorithm.mp4

03:06

04 - Quantization and The Sampling Theorem

001 Nyquist Theorem ( Sampling Theorem ).mp4

09:24

002 The Passive Low-Pass Filter.mp4

07:30

003 The Passive High-Pass Filter.mp4

04:48

004 The Active Filter.mp4

05:49

005 The Bessel, Chebyshev and Butterworth filters.mp4

06:44

05 - Linear Systems and Superposition

001 Introduction to Linear Systems.mp4

04:47

002 Understanding Superposition.mp4

05:00

003 Impulse and Step Decomposition.mp4

04:31

06 - Convolution

001 Introduction to Convolution.mp4

03:22

002 The Convolution Operation.mp4

06:44

003 Examinging the Output of Convolution.mp4

04:45

004 The Convolution Sum Equation.mp4

02:05

005 A Closer look at the Delta function.mp4

05:41

006 0-Examine-signals.zip

006 Coding Examining the signals.mp4

07:19

006 mysignals.zip

007 1-Convolution-v1.zip

007 Coding Computing the convolution of two signals.mp4

07:07

008 1-Convolution-v2.zip

008 Coding Developing the Convolution algorithm.mp4

21:11

009 2-Deconvolution.zip

009 Coding Computing the De-convolution of two signals.mp4

06:19

010 3-Correlation.zip

010 Coding Correlation.mp4

07:17

010 mysignals.zip

011 The Identity property of convolution.mp4

01:30

012 The Running Sum and First Difference.mp4

01:55

013 5-Running-Sum.zip

013 Coding Computing the running sum of a signal.mp4

08:04

014 5-Running-Sum-v2.zip

014 Coding Developing the Running Sum algorithm.mp4

06:53

015 6-First-Difference.zip

015 Coding Computing the First Difference of a signal.mp4

03:12

016 6-First-Difference-v2.zip

016 Coding Developing the First Difference algorithm.mp4

06:27

07 - Fourier Transform

001 Introduction to Fourier Analysis.mp4

05:29

002 The DFT Engine.mp4

04:11

003 Understanding Forward and Inverse DFT.mp4

04:32

004 1-DFT.zip

004 Coding Developing the Discrete Fourier Transform (DFT) algorithm.mp4

15:53

004 mysignals.zip

005 2-DFT-magnitude.zip

005 Coding Developing the DFT magnitude algorithm.mp4

10:03

006 3-IDFT.zip

006 Coding Developing the Inverse Discrete Fourier Transform (IDFT) algorithm.mp4

20:35

007 4-IDFT-ecg.zip

007 Coding Computing the IDFT of an ECG signal.mp4

05:25

008 Symmetry between Time domain and frequency domain -Duality.mp4

00:55

009 Polar Notation.mp4

02:50

010 Introduction to Spectral Analysis.mp4

02:31

011 The Frequency Response.mp4

03:34

08 - Complex Numbers

001 The Complex Number System.mp4

02:05

002 Polar Representation of Complex Numbers.mp4

01:35

003 Eulers Relation.mp4

01:35

004 Representation of Sinusoids.mp4

01:57

005 Representing Systems.mp4

01:34

09 - Complex Fourier Transform

001 Introduction to Complex Fourier Transform.mp4

01:43

002 Mathematical Equivalence.mp4

01:38

003 The Complex DFT Equation.mp4

00:36

004 Comparing Real DFT and Complex DFT.mp4

03:17

10 - Fast Fourier Transform (FFT)

001 An Overview of how FFT works.mp4

08:17

002 Understanding the complexity of calculating DFT directly.mp4

02:35

003 How the Decimation -in-Time FFT Algorithm works.mp4

09:00

004 Coding Computing the FFT of a signal.mp4

11:51

004 fft.zip

004 mysignals.zip

11 - Digital Filter Design

001 Introduction to Digital Filters.mp4

03:14

002 The Filter Kernel.mp4

01:49

003 The Impulse,Step and Frequency response.mp4

01:16

004 Understanding the Logarithmic scale and decibels.mp4

02:59

005 Information representations of a signal.mp4

03:57

006 Time domain parameters.mp4

04:20

007 Frequency domain parameters.mp4

01:25

008 Designing digital filters using the spectral inversion method.mp4

04:37

009 Designing digital filters using the spectral reversal method.mp4

02:50

010 Classification of digital filters.mp4

01:56

12 - Designing Finite Impulse Response (FIR) Filters

001 The Moving Average Filter.mp4

04:11

002 The Multiple Pass Moving Average Filter.mp4

02:20

003 The Recursive Moving Average Filter.mp4

04:33

004 1-median-filter.zip

004 Coding Smoothing signals with the median filter.mp4

07:19

005 Coding FIR filter application project (Part I).mp4

07:59

006 Coding FIR filter application project (Part II).mp4

12:09

007 2-filtfilt.zip

007 Coding FIR filter application project (Part III).mp4

08:18

13 - Designing Infinite Impulse Response (IIR) Filters

001 Introduction to Recursive Filters.mp4

00:46

002 The Recursion Equation.mp4

01:50

003 1-freqz.zip

003 Coding Computing the frequency response of a filter.mp4

05:14

004 2-cheby1.zip

004 Coding Computing the frequency response of a Type I Chebyshev Bandpass Filter.mp4

05:01

005 1-butter.zip

005 Coding Creating a Butterworth lowpass filter.mp4

05:21

006 2-cbeby1.zip

006 Coding Creating a Type I Chebyshev lowpass filter.mp4

06:30

007 3-cbeby2.zip

007 Coding Creating a Type II Chebyshev lowpass filter.mp4

04:15

008 4-elliptic.zip

008 Coding Creating an Elliptic lowpass filter.mp4

05:46

009 5-bessel.zip

009 Coding Creating a Bessel lowpass filter.mp4

06:09

010 Coding IIR filter application project -Butterworth filter (Part I).mp4

07:13

011 Coding IIR filter application project -Butterworth filter (Part II).mp4

10:53

012 9-Butterwoth-implementation.zip

012 Coding IIR filter application project -Butterworth filter (Part III).mp4

06:38

013 Coding Designing an FIR filter with a Kaiser Window (Part III).mp4

04:42

014 The Single-Pole Recursive Filter.mp4

02:52

015 Digital Chebyshev Filters.mp4

01:57

14 - Designing Windowed Filters

001 Introduction to Windowed-Sinc Filters.mp4

00:47

002 The Sinc Function and the Truncated Sinc Filter.mp4

03:15

003 The Blackman window.mp4

01:00

004 The Hamming and Blackman window equations.mp4

02:34

005 Designing the Windowed Sinc filter.mp4

02:34

006 Coding Designing an FIR filter with a Kaiser Window (Part I).mp4

12:15

007 10-fir-filter-implemetation.zip

007 Coding Designing an FIR filter with a Kaiser Window (Part II).mp4

09:56

008 3-get-window.zip

008 Coding Generating windows.mp4

08:27

009 1-barthan.zip

009 Coding Creating the Barlett-Hann Window.mp4

05:27

010 2-bartlett.zip

010 Coding Creating the Barlette Window.mp4

01:14

011 3-blackman.zip

011 Coding Creating the Blackman Window.mp4

01:10

012 3-blackman-harris.zip

012 Coding Creating the Blackman-Harris Window.mp4

01:29

013 4-bohman.zip

013 5-boxcar.zip

013 6-chebwin.zip

013 7-cosine.zip

013 Creating Bohman,Boxcar, Chebyshev, Cosine ,Flattop and Gaussian Windows.mp4

06:27

014 10-hamming.zip

014 11-Hann.zip

014 Coding Creating the Hamming and Hanning Windows.mp4

01:42

015 12-kaiser.zip

015 Coding Creating the Kaiser Window.mp4

01:33

016 13-nuttall.zip

016 14-parzen.zip

016 Coding Creating the Nuttall and Parzen Windows.mp4

02:09

017 15-slepian.zip

017 16-traing.zip

017 Coding Creating the Slepian and the Triangular Window.mp4

02:55

15 - Custom Filters

001 Coding Experimenting with the Forward-Backward filter.mp4

11:47

002 4-detrend.zip

002 Coding De-trending a signal.mp4

06:54

003 Coding Comparing the performance of different Scipy filters (Part I).mp4

05:28

004 11-filtfilt-vs-lfilter.zip

004 Coding Comparing the performance of different Scipy filters (Part II).mp4

08:06

005 3-remez.zip

005 Coding Computing the frequency response of a Remez filter.mp4

07:02

16 - Designing Match Filters

001 4-Correlation-Match-Filter-Implementation.zip

001 Coding Building a match filter with cross-correlation.mp4

16:22

17 - FFT Convolution

001 Understanding how the Overlap-Add method works.mp4

04:09

002 Understanding how FFT-Convolution works.mp4

04:04

18 - Representing Linear Time Invariant (LTI) )Systems in Python

001 1-Transfer-Functions.zip

001 Coding Creating a Transfer Function.mp4

06:11

002 2-ZeroesPolesGain.zip

002 Coding ZerosPolesGain.mp4

04:53

003 3-freqresponse.zip

003 Coding Frequency response of a LTI.mp4

05:44

004 4-bode.zip

004 Coding Computing the bode plot of a LTI system.mp4

04:16

005 5-Impulse.zip

005 Coding Computing the impulse response of a LTI system.mp4

03:51

19 - Interpolation

001 5-interpolation.zip

001 Coding Linear and cubic interpolation.mp4

07:38

002 6-UnivariateSpline.zip

002 Coding Working with splines.mp4

10:30

003 7-rbf.zip

003 Coding Comparing Rbf with UnivariateSpline.mp4

10:32

20 - Waveform Generation

001 Coding Generating a gausspulse.mp4

05:34

002 Coding Generating square waves and pulse-width modulated sine waves.mp4

08:07

Description

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

What You'll Learn?

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

Who is this for?

People working in the field of signal processing

University students taking classes in signal processing

Python developers who wish to expand their skills

People who want to understand signal processing practically and apply it to their respective fields.

What You Need to Know?

You will need just a good working computer for this course

More details

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 avoidingÂ 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 architectureÂ 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,Â develop 17 differentÂ typesÂ of windowÂ 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,Â 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.
Who this course is for:
People working in the field of signal processing
University students taking classes in signal processing
Python developers who wish to expand their skills
People who want to understand signal processing practically and apply it to their respective fields.

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Professional embedded firmware developer. Been doing this for years, can't even remember when it started. My areas of expertise include real-time systems development, low level development, medical device architecture, embedded signal processing and embedded AI. Most of my work is based on Arm Cortex-Microcontrollers. And Oh! I am a normal guy.

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