Evenet 2000: Designing and Training Arbitrary Neural Networks in Java
In this paper, Evenet-2000, a Java-Based neural network toolkit is presented. It is based on the representation of an arbitrary neural network as a block diagram (these blocks are, for example, summing junctions or branch points) with a set of simple manipulation rules. With this toolkit, users can...
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Format: | Buchkapitel |
Sprache: | eng |
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Zusammenfassung: | In this paper, Evenet-2000, a Java-Based neural network toolkit is presented. It is based on the representation of an arbitrary neural network as a block diagram (these blocks are, for example, summing junctions or branch points) with a set of simple manipulation rules. With this toolkit, users can easily design and train any arbitrary neural network, even time-dependent ones, avoiding the complicated calculations that the means of establishing the gradient algorithm requires when a new network architecture is designed. Evenet-2000 consists of three parts: a calculation library, a user-friendly interface and a graphic network editor with all the Java advantages: encapsulation, inheritance, powerful libraries... |
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ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/3-540-45723-2_12 |