Abstract
Adaptive or self-optimizing systems utilize feedback principles to achieve automatic performance optimization. These principles have been applied to both control systems and adaptive logic structures. The Adaline (adaptive linear threshold element) is essentially the same as an adaptive sampled-data system with quantized input and output signals. A digital controller made of adaptive neurons comprises a pattern-recognizing control system. When the state of a control system is represented as a pattern, learning to make the control decisions actually becomes the same as learning to classify the patterns.

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