Neural controller code matlab software: Neural Network Toolbox for MATLAB & Simulink, Matlab 7, Matlab Getting Started, Matlab Demy, Matlab 7, Matlab Getting Started, Matlab Demy and more.
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Homepage: http://www.nd.com |
| Type: Demo |
Releases: Sep 10, 2004 |
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| Cost: $795.00US |
Developer: NeuroDimension, Inc. |
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The NeuroSolutions for MATLAB neural network toolbox is a valuable addition to MATLAB's technical computing capabilities allowing users to leverage the power of NeuroSolutions (www.neurosolutions.com) inside MATLAB and Simulink. The toolbox features 15 neural models, 5 learning algorithms and a host of useful utilities integrated in an easy-to-use interface, which requires ?next to no knowledge? of neural networks to begin using the product. |
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Homepage: http://www.majorfeeling.com |
| Type: Shareware |
Releases: Aug 18, 2005 |
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| Cost: $50.00US |
Developer: majorfeeling.com |
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PIDWell provides six structures of universally used PID controllers:
1. General PID Controller
2. PID Controller with Integration Separation
3. Anti-Windup PID Controller
4. PID Controller with Partial Differential
5. PID Controller with Differential in Advance
6. PID Controller with Dead Zone
The user can design PID-controller-based real-time control system according to control scenario and performance specifications. |
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Homepage: visit |
| Type: Freeware |
Releases: Jun 08, 2011 |
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| Cost: $0.00US |
Developer: Guide to Matlab |
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Guide to Matlab, Matlab 7, Matlab Getting Started, Matlab Demystified, Matlab for Engineers |
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Homepage: visit |
| Type: Freeware |
Releases: Jun 08, 2011 |
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| Cost: $0.00US |
Developer: Matlab 7 Getting Started |
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Matlab 7, Matlab Getting Started |
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Homepage: visit |
| Type: Freeware |
Releases: Jun 08, 2011 |
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| Cost: $0.00US |
Developer: Signals and Systems |
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Signals and Systems, Guide to Matlab, Matlab 7, Matlab Getting Started, Matlab Demystified, Matlab for Engineers |
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Homepage: http://www.rgsoftware.com |
| Type: Demo |
Releases: Jan 01, 2000 |
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| Cost: $240.00US |
Developer: RG Software Corporation |
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Artificial Neural Networks are computational paradigms which implement simplified models of their biological counterparts, biological neural networks. Biological Neural Networks are the local assemblages of neurons and their dendrite connections that form the brain. The implementation of Neural Networks for brain-like computations like patterns recognition, decisions making, motory control and many others is made possible by the advent... |
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Homepage: visit |
| Type: Freeware |
Releases: Jun 08, 2011 |
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| Cost: $0.00US |
Developer: Matlab for engineers |
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Matlab 7, Matlab Getting Started, Matlab Demystified, Matlab for Engineers |
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Homepage: http://www.easynn.com |
| Type: Shareware |
Releases: Jan 16, 2004 |
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| Cost: $39.00US |
Developer: Neural Planner Software |
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NeuroDiet is a neural network application that learns how the foods you eat are related to your health and fitness. All the neural network functions are managed automatically. You don't need to know anything about neural networks. All you need to do is tell NeuroDiet how your symptoms are changing and which foods you are eating. Every day NeuroDiet will produce a list of foods that may be causing problems with your health and fitness. |
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Homepage: http://www.easynn.com |
| Type: Shareware |
Releases: Aug 04, 2001 |
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| Cost: $29.00US |
Developer: Neural Planner Software |
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EasyNN is a neural network system for Microsoft Windows. It makes the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files. The user can produce training, validating and querying files using the facilities in EasyNN or using any editor, word processor or spreadsheet that supports text files. |
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Homepage: http://www.sharktime.com/ |
| Type: Freeware |
Releases: Jul 10, 2009 |
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| Cost: $0.00US |
Developer: SharkTime Software |
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Neural network classification results live view (like a movie). Free software for playing with neural networks classification. Features: Easy, ready to play with, many network architectures, different shapes of training data sets, learning with backpropagation algorithm, optional momentum. For better understanding of neural networks. |
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