Abstract
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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González, E.J., Hamilton, A.F., Moreno, L., Sigut, J.F., Marichal, R.L. (2001). Evenet 2000: Designing and Training Arbitrary Neural Networks in Java. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_12
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DOI: https://doi.org/10.1007/3-540-45723-2_12
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