Chaos-based Learning
نویسنده
چکیده
It is demonstr ated th at the chaotic properties of neural networks (in this case networks defined by the generalized delta procedur e) can be used to improve th eir learning performance. By adapt ively varying the learning-rate parameter an annealing mechanism can be introduced that is founded in chaos. T he prop osed mechanism, chaos-based learning, provides faster convergence than standard back-propagation and also seems to provide a computationally less intensive alternative to other back-propagation accelera ting techniques by using adaptive step-size control.
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عنوان ژورنال:
- Complex Systems
دوره 5 شماره
صفحات -
تاریخ انتشار 1991