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Train and Analyze Neural Networks to
Fit Your Data
 Artificial neural networks have revolutionized the way
researchers solve many complex and real-world
problems in engineering, science, economics, and
finance. Neural Networks capitalizes on the
computational power and flexibility of
Mathematica to help you utilize this
cutting-edge technology.
Neural Networks is equally suited for advanced
and inexperienced users. The built-in palettes
facilitate the input of any parameter for the
analysis, evaluation, and training of your data. The
online documentation contains a number of detailed
examples that demonstrate different neural network
models. You can solve many problems simply by
applying the example commands to your own data.
Neural Networks also provides numerous options
to modify the training algorithms. The default
values have been set to give good results for a
large variety of problems, allowing you to get
started quickly using only a few commands. As you
gain experience, you will be able to customize the
algorithms to improve the performance, speed, and
accuracy of your neural network models.
Neural Networks gives professionals and
students the tools to train, visualize, and validate
neural network models. It supports a comprehensive
set of neural network structures--including radial
basis function, feedforward, dynamic, Hopfield,
perceptron, vector quantization, unsupervised, and
Kohonen networks. It implements state-of-the-art
training algorithms like Levenberg-Marquardt,
Gauss-Newton, and steepest descent. Neural
Networks also includes special functions to
address typical problems in data analysis, such as
function approximation, classification and
detection, clustering, nonlinear time series, and
nonlinear system identification problems.
With Neural Networks and Mathematica,
you will have access to a robust modeling
environment that lets you test and explore neural
network models faster and easier than ever before.
The package comes with printed and electronic
documentation.
Special features:
Click here to visit official website
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