On a Class of Constructible Neural Networks
نویسنده
چکیده
We propose a new class of artiicial neural networks for regression tasks and its construction algorithm. These networks have two diierent but isomorphic layouts. The tree-structured layout is used and built up during the construction phase and it can be used for accelerated serial evaluation of the network. The three-layer layout can be derived from the tree-structured layout by a simple mapping. It is used for an implementation of the network on parallel hardware. The network construction algorithm is a combination of ideas from statistics and neural network theory and it can be parallelized easily.
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تاریخ انتشار 1995