Acta Scientiarum Naturalium Universitatis Pekinensis

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A Discussion of the Learning in a Simple Perceptron

FENG Jianfeng   

  1. Dept. of Probability and Statistics, Peking University, Beijing, 100871
  • Received:1994-07-24 Online:1995-01-20 Published:1995-01-20



  1. 北京大学概率统计系,北京,100871

Abstract: We extend the convergence of the simple perceptron learning rule to the case that the set of inputs is infinity or a region. When the set of inputs is linearly separable, we prove that a simple perceptron always improves its performance. As the set of the inputs is 'strong' linearly separable, then within finite time the connections among units converge to a limit which separates the inputs. The convergence rate is also estimated.

Key words: simple perceptron, supermartingale, linearly separable

摘要: 当输入是无穷集或区域时,通过构造一个上鞅,本文证明了简单Perceptron学习算法的收敛性。

关键词: 简单Perceptron, 上鞅, 线性可分

CLC Number: