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ATOMS : Neural Network Module details
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Neural Network Module

This is a Scilab Neural Network Module which covers supervised and unsupervised training algorithms
(385 downloads for this version - 16548 downloads for all versions)
Details
Version
3.0
Author
Tan Chin Luh
Owner Organization
ByteCode Asia
Maintainers
Chin Luh Tan
Administrator Atoms
Yann Debray
License
Creation Date
May 29, 2020
Source created on
Scilab 6.1.x
Binaries available on
Scilab 6.0.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit MacOSX
Scilab 6.1.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit MacOSX
Install command
--> atomsInstall("neuralnetwork")
Description
            This Neural Network Module is based on the book "Neural Network
Design" book by Martin T. Hagan. 

The module could be used to build following netwroks
1. Perceptron
2. Adaline
3. Multilayer Feedforware Backpropagation Network
   - Gradient Decent
   - Gradient Decent with Adaptive Learning Rate
   - Gradient Decent with Momentum
   - Gradient Decent with Adaptive Learning Rate and Momentum
   - Levenberg–Marquardt
4. Competitive Network
5. Self-Organizing Map
6. LVQ1 Network

New in ver 3.0: 
1. Feed-forward Back-Propagation Network Base on Andrew Ng's Coursera
Deep-Learning Specialization Course.
2. Updated demos
3. Update for Scilab 6.1            
Files (3)
[1.28 MB]
OS-independent binary for Scilab 6.0.x

[1.27 MB]
OS-independent binary for Scilab 6.1.x

[868.98 kB]
Source code archive

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