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Video 63: Comparison of Threshold Estimation Methods for Wavelet based Denoising of Audio Signals (with MATLAB Code)

Hello Viewers. In this video, a comparative study is shown to help us in selecting best combination of thresholding method, wavelet function and level of decomposition for denoising of audio of some Indian musical instruments.
This video includes following components,
• Introduction to denoising using wavelets.
• Various Noise estimation and Threshold Selection methods.
• MATLAB implementation (with MATLAB code).
• Applying these methods on audio of some Indian musical instruments.
• Comparative study and Result Analysis.
Wavelet transform is a very powerful tool in the field of Signal Denoising. It gives far better denoising results as compared to frequency selective filters.

Links of previous videos.

1. Introduction to Wavelet Theory and Its Applications: Click Here

2. Wavelet based denoising of audio signals using MATLAB and SIMULINL: Click Here

3.  Wavelet Based Denoising of 1D Signals using Python: Click Here

Video 62: Color Edge Features and DWT based Image Retrieval (With MATLAB Code)

Hello viewers, in this video, Content Based Image Retrieval (CBIR) is implemented. This CBIR utilizes both the color and edge features of the images. For this purpose, Color Edge Histograms are obtained. To reduce the size of feature vector, Discrete Wavelet Transform (DWT) is also used. The simulation results show the effectiveness of the proposed algorithm for effective CBIR.

This video includes following contents,

* Introduction to Content Based Image Retrieval (CBIR).
* Color Edge Feature (Proposed  Algorithm).
* Finding Feature Vector (Training Process).
* Testing Process.
* MATLAB implementation (with MATLAB code).
* Result Analysis.

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Color Layout Descriptor (CLD) of MPEG7 for Image Retrieval: Click Here

2. Previous video:
Edge Histogram Descriptor (EHD) of MPEG7 for Image Retrieval: Click Here

3. Previous video:
Content Based Image Retrieval (CBIR) using Wavelet features, CLD and EHD of MPEG7: Click Here

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Video 61: Time Series Prediction using ANFIS (With MATLAB Code)

Hello viewers, in this video, The Time Series Prediction using Adaptive Neuro-Fuzzy Inference System (ANFIS) is explained. The time series taken here is Mackey-Glass chaotic time series, which is considered as benchmark problem. The ANFIS based algorithm for time series prediction is explained in detail.

This video includes following contents,

* Introduction to time-series prediction.
* ANFIS for time-series prediction.
* Mackey-Glass chaotic time series (A benchmark).
* Time series prediction algorithm using ANFIS.
* MATLAB implementation (with MATLAB code).
* Result Analysis.

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Video 60: ANFIS: Neuro-Fuzzy Inference System (Theory and MATLAB Implementation)

Hello viewers, in this video, The Neuro-Fuzzy modelling highlighting ANFIS is explained. The basic theory of ANFIS is presented. Also the complete process of MATLAB implementation is given. In MATLAB implementation, the ANFIS is used as universal approximator. The two functions 1D sin(t) and 2D sin(r)/r are realized using ANFIS.

This video includes following contents,

• Neuro – Fuzzy Modelling.
• Adaptive Neuro-Fuzzy Inference System (ANFIS).
• ANFIS Architecture.
• ANFIS Hybrid learning algorithm.
• ANFIS Applications.
• ANFIS as Universal Approximator (UA).
• MATLAB Implementation of ANFIS as UA (with MATLAB code).

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Video 59: Understanding Fuzzy Logic Controllers (Theory and MATLAB Implementation)

Hello viewers, in this video, Fuzzy Logic Controller (FLC) is explained. Along with basic theory, the complete FLC design steps are explained. An FLC for steam throttle control is designed. Also the complete process of MATLAB implementation is explained.

This video includes following contents,

* Why need controllers?
* Classical controller and Fuzzy logic controller (FLC).
* Inside Fuzzy Logic Controller (FLC).
* Design of FLC for a throttle control system.
* Fuzzification.
* Rule base implementation.
* De-fuzzification.
* Simulation of designed FLC using MATLAB.

Video 58: Transform Basics (Concepts of Orthogonal, Bi-orthogonal vectors, Basis functions & Transforms)

Hello viewers, in this video, basic background of vector algebra is explained which will help the viewer to understand how transforms are evolved. The veiwer will learn about vector inner product, vector norm, orthogonal, orthonoroml, bi-orthogonal vectors and basis functions. Also it is explained how the basis functions can create a transforms.

This video includes following contents,
• Vector inner product.
• Orthogonal vectors.
• Orthogonal and Orthonormal basis functions.
• Bi-Orthogonal and Bi-Orthonormal basis functions.
• Evolution of Transform and creating transformation matrix.
• 1D and 2D Orthogonal transforms (Real and Complex).
• 1D and 2D Bi-Orthogonal Transforms (Real and Complex).
• Numerical examples of various transforms.
• Some popular transforms.