- Deep Learning
- Deep Learning for Image Recognition
- Object Classification in Photographs
Projects
Showing 1–10 of 13 results
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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 -
Artificial Neural Networks, Machine Learning, Projects
Artificial neural networks to passive acoustical identification of animals
Artificial Neural Networks, Machine Learning, ProjectsArtificial neural networks to passive acoustical identification of animals
In this project, MATLAB codes have been developed by MATLAB4Engineers team. Algorithms such as Extreme Learning Machine (ELM), Multi-Layer Perceptron (MLP), and different strategies for features extraction has been implemented and tested in MATLAB.
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Electric Circuits, Projects
Electrical circuits analysis
MATLAB is a numeric computation software for engineering and scientific calculations. MATLAB is increasingly being used by students, researchers, practicing engineers and technicians. The causes of MATLAB popularity are
legion. Among them are its iterative mode of operation, built-in functions, simple programming, rich set of graphing facilities, possibilities for writing additional functions, and its extensive tool boxes.SKU: n/a -
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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