Video 55: Discrete Fourier Transform (DFT) of 1-D Signals

 

Hello viewers, In this video, the basic theory of Discrete Fourier Transform (DFT) is presented. It includes background of DTFT and evolution of DFT from DTFT. It also explains that how DFT can be expressed as linear transformation for easy calculation of forward DFT and inverse DFT. Also computational complexity of DFT/ IDFT calculation is discussed and compared with FFT. The MATLAB implementation is also given by which one can find N-point DFT of any real sequence of any length. This video includes following topics,

* Introduction to Discrete Time Fourier Transform (DTFT).

* Need of Discrete Fourier Transform (DFT).

* DFT Computation method.

* DFT as linear transformation.

* Algorithm complexity.

* MATLAB Code to find N-point DFT of any sequence.

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Link of previous video

Discrete Fourier Transform (DFT) of images and image filtering: Click Here

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Video 54: Face Recognition using Wavelet Features and PCA (With MATLAB Code)

Hello viewers, In this video, a face recognition scheme is implemented using Wavelet Features and Principal Component Analysis (PCA). Here wavelets are used to extract facial features and PCA is used to reduce the size of wavelet feature vectors. The proposed scheme is very robust and capable to recognize the faces even some changes occur in faces such growing beard and mustache or putting goggles etc.

This video covers followings contents,

• Face image database (Faces94).
• Face image database preparation for training and testing.
• Finding wavelet features.
• PCA for dimension reduction.
• Training and testing procedures.
• MATLAB Code for Training.
• MATLAB Code for Testing (Discrete and Bulk).

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Links of previous videos:

1. Principal Component Analysis (PCA) for Images and Signals: Click Here

2. Face Recognition using PCA in MATLAB: Click Here

Links for Face Image Database:

1. https://cmp.felk.cvut.cz/~spacelib/faces/ (All Faces)

2. https://cmp.felk.cvut.cz/~spacelib/faces/faces94.html (Face94 database)

3. https://www.exptech.co.in/p/resource-download.html (Database used in video)

Download Resources:

1. All Image Database: Download

2. Test Images for Robustness: Download

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Video 53: ECG based Heart Disease Diagnosis using Wavelet Features and Deep CNN (Arrhythmia detection)

Hello viewers. This is recorded video of an invited guest lecture delivered by me in an international conference held in July 2021.

This video is about heart disease diagnosis using wavelet features and deep CNN mainly focusing on Arrhythmia detection and heart rate estimation.

This video includes following contents.

• Introduction (Problem Statement).
• Basics of ECG signals and QRS Complex. 
• ECG Database on PhysioNet.
• Proposed wavelet based algorithm for Heart Rate estimation and Arrhythmia detection.
• Deep CNN based approach of Arrhythmia detection.
• Conclusions.

This lecture is based on my previously published YouTube videos, which you can find on following links.

1. ECG signals Classification using CWT and Deep Neural Network in MATLAB: Click Here
2. ECG's QRS Peak Detection and Heart Rate Estimation using Discrete Wavelet Transform (DWT) in MATLAB: Click Here

Other Links:

1. PhysioNet: https://physionet.org/

2. PhysioNet Databases: https://physionet.org/about/database/

3. PhysioNet Bank ATM: https://archive.physionet.org/cgi-bin/atm/ATM

4. ECG signal database GitHub repository:

     https://github.com/mathworks/physionet_ECG_data/

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Video 52: LTI System Analysis using Python (With Python Code)

 

Hello Viewers, In this video, the introduction to LTI systems is described. Also various time domain and frequency domain analysis of LTI systems are implemented using Python. The Python program can plot various time response curves such as Impulse response, Step response and Ramp response. It can also give various stability plots such as Root locus, Nyquist plot, Bode plot, Log magnitude vs Phase plot (Nichols Plot) and Pole-zero plot.

The Python implementation is done using Spyder IDE in Anaconda environment. The Python Control System Library (v0.9.0) is used to write Python program.

This video includes following contents:

• Introduction to LTI systems.
• Various (Time domain/ Freq. domain) analysis of LTI systems.
• Anaconda and Spyder for Python implementation.
• Python Control System Library (v0.9.0).
• Python code for LTI System Analysis.

Link for previous video,

1. LTI System Analyzer using MATLAB GUI: Click Here

Other Links:

1. Anaconda Download: https://www.anaconda.com/distribution/

2. Spyder IDE: https://www.spyder-ide.org/

3. Python Control System Library (0.9.0): https://python-control.readthedocs.io/en/0.9.0/index.html

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Video 51: Solution of State Equations (Homogeneous & Nonhomogeneous) with MATLAB Simulation

 

Hello Viewers, in this video, the theory of solution of state equations is explained. Both the cases of homogeneous and non-homogeneous equations are considered. To clear the concept, some numerical examples are also solved. Also a MATLAB code is developed which is very efficient and capable to solve any state equations for any types of inputs. With this MATLAB program, students can solve questions of their text books and can verify their theoretical outcomes.

This video includes following contents:

• State Space model of systems.
• Solution of homogeneous state equation.
• State Transition Matrix (STM) and its properties.
• Example of solution of homogeneous state equation.
• Solution of non-homogeneous state equation.
• Examples of solution of non-homogeneous state equation.
• MATLAB code for solution of state equations.

Link for previous videos,

1. Introduction to State Space Analysis: Click Here

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Video 50: Introduction to State Space Analysis (Physical Systems Modelling) (With MATLAB Code)

 

Hello Viewers, in this video, the theory of state space modelling is explained. the modern approach based on state space is compared with classical approach of system modelling which is based on transfer functions highlighting advantages of state space method.

Also various physical systems such as Electrical and Mechanical systems are considered for state space modelling. 

The relationship between TF and SS for an LTI system is also established. Also a MATLAB code is explained to model a system in SS and to do various analysis of it.

This video includes following contents:

• Why State Space? (Classical and Modern approach of system modelling).
• Introduction to State space system modelling.
• Basic Definitions: State variables, State, State vector and State space.
• State space modelling of physical systems (Mechanical/ Electrical).
• State space to transfer function conversion and vice-versa. 
• MATLAB code for State space modelling.

Link for previous videos,

1. LTI System Analyzer using MATLAB GUI: Click Here

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