Teaching Feed-Forward Neural Networks by Simulated Annealing
نویسنده
چکیده
Simulated ann ealing is applied to the problem of teachin g feed-forward neural networks with discret e-valued weights . Network performance is optimized by repea ted present ation of tr aining data at lower and lower temperatures. Several examples, including the parity and "clump-recognition " problem s are treated, scaling with network complexity is discussed , and the viabilit y of mean -field approximations to the annealing pro cess is considered.
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ورودعنوان ژورنال:
- Complex Systems
دوره 2 شماره
صفحات -
تاریخ انتشار 1988