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NEURAL NETWORKS with MATLAB
Marvin L.How much do you like this book?
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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. The more importan features are de next: •Deep learning, including convolutional neural networks and autoencoders •Parallel computing and GPU support for accelerating training (with Parallel Computing Toolbox •Supervised learning algorithms, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and recurrent neural network (RNN) •Unsupervised learning algorithms, including self-organizing maps and competitive layers •Apps for data-fitting, pattern recognition, and clustering •Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance •Simulink blocks for building and evaluating neural networks and for control systems applications
Categories:
Year:
2016
Publisher:
CreateSpace Independent Publishing Platform
Language:
english
Pages:
231
ISBN 10:
1539701956
ISBN 13:
9781539701958
File:
PDF, 2.05 MB
Your tags:
IPFS:
CID , CID Blake2b
english, 2016
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