Neural Network Toolbox

Key Features

  • Supervised networks, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and layer-recurrent
  • Unsupervised networks, including self-organizing maps and competitive layers
  • Apps for data-fitting, pattern recognition, and clustering
  • Parallel computing and GPU support for accelerating training (using Parallel Computing Toolbox)
  • 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
  • Simulink® blocks for building and evaluating neural networks and for control systems applications

Getting Started with Neural Network Toolbox 4:20
Use graphical tools to apply neural networks to data fitting, pattern recognition, clustering, and time series problems.

Next: Data Fitting, Clustering, and Pattern Recognition

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画像処理とコンピュータービジョンのための機械学習 -MATLABによる自動認識-

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