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Neural Network Toolbox for MATLAB
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  • Title Neural Network Toolbox for MATLAB
  • Author(s) Howard Demuth, Mark Beale
  • Publisher: The MathWorks, Inc. (2002)
  • Hardcover/Paperback ???
  • eBook PDF (840 pages, 5.6 MB)
  • Language: English
  • ISBN-10/ASIN: B0006P1NU0
  • ISBN-13: N/A
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Book Description

Neural networks are composed of simple elements operating in parallel. These elements are inspired by biological nervous systems. As in nature, the network function is determined largely by the connections between elements.

We can train a neural network to perform a particular function by adjusting the values of the connections (weights) between elements.

Neural Network Toolbox provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.

The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox™.

About the Authors
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