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- 247kb
- Update:
- 2012-11-26
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Description: Key Features
* Neural network design, training, and simulation
* Pattern recognition, clustering, and data-fitting tools
* Supervised networks including feedforward, radial basis, LVQ, time delay, nonlinear autoregressive (NARX), and layer-recurrent
* Unsupervised networks including self-organizing maps and competitive layers
* Preprocessing and postprocessing for improving the efficiency of network training and assessing network performance
* Modular network representation for managing and visualizing networks of arbitrary size
* Routines for improving generalization to prevent overfitting
* Simulink® blocks for building and evaluating neural networks, and advanced blocks for control systems applications
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