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- Deep Learning
- Deep Learning for Image Recognition
- Object Classification in Photographs
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Image Processing, Projects
Mouse Pointer Control using Color Detection in MATLAB
This program controls the functions of mouse pointer by detecting red, green and blue colored caps.
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Projects, Signal Processing
ADAPTIVE LINEAR ELEMENT (ADALINE) – SIGNAL PROCESSING
The ADALINE (adaptive linear neuron) networks applied in this project are similar to the perceptron, but their transfer function is linear rather than hard-limiting. This allows their outputs to take on any value, whereas the perceptron output is limited to either 0 or 1. Both the ADALINE and the perceptron can solve only linearly separable problems. However, here the LMS (least mean squares) learning the rule, which is much more powerful than the perceptron learning rule, is used. The LMS, or Widrow-Hoff, learning rule minimizes the mean square error and thus moves the decision boundaries as far as it can from the training patterns.
In this project, you design an adaptive linear system that responds to changes in its environment as it is operating. Linear networks that are adjusted at each time step based on new input and target vectors can find weights and biases that minimize the network’s sum-squared error for recent input and target vectors. Networks of this sort are often used in error cancellation, signal processing, and control systems.SKU: n/a -
Energy Systems, Projects, Renewable Energy, Solar Systems
MODELING AND SIMULATION OF PV SOLAR SYSTEM
Photovoltaic solar power technology is being pushed to the forefront as a viable alternative source of renewable energy. Addressing the key design challenges involved in the development and implementation of these systems requires simulation tools capable of not only modeling and analyzing the behavior of diverse electronic components but also the ability to combine them with the associated control algorithms and evaluate the full system performance.
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Machine Learning, Projects
FACE RECOGNITION USING PRINCIPLE COMPONENT ANALYSIS USING MATLAB
This program recognizes a face from a database of human faces using PCA. The principal components are projected onto the eigenspace to find the eigenfaces and an unknown face is recognized from the minimum euclidean distance of projection onto all the face classes. Watch videos
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Cobus Bester –
A wonderful collection of matlab4engineers team! A must buy for all matlab4engineers fans.
Cobus Bester –