Network input-output devices {Perceptron} can alter connections or connection strengths by adjusting weights based on input, using feedback that output was correct or incorrect compared to ideal output {Perceptron learning rule}. Ideal output is one pattern or separable linear patterns. In initial learning period, Perceptrons adjust weights. In later test period, Perceptrons send more or less correct output for inputs.
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Date Modified: 2022.0224