【摘要】 深入分析了ＢＰ（Ｂａｃｋ—Ｐｒｏｐａｇａｔｉｏｎ）算法的缺陷，在ＢＰ算法的基础上， 提出逐层训练多层网络的快速算法，主要精神是：ａ）逐层地训练多层网络而不是一起训 练；ｂ）对隐单元层给以具体指导；ｃ）根据具体问题给予合适的权重分配规则即合适的 “能量函数”；ｄ）保持ＢＰ算法的优点。对一些问题的训练速度与ＢＰ算法比较有几个 数量级的提高。这一算法还可对多层网络的运行机制作一些研究．更多还原

【Abstract】 Artificial-Neural Network (ANN) is a complex network system composed of many simple elements connected extensively each other and can be regarded as a simulation or abstraction of biological neural system. Multi-Layer Network (MLN ) is one of the most important ANN. A essential algorithm to train MLN is BP (Back-Propagation ) algorithm. Based on BP algorithm, a hgih-speed algorithm-train MLN layer-by-layer algorithm is proposed with main points: 4 ) train MLN layer-by-layer instead of all together; b ) giving instruction to hidden units; c) giving appropriate "energy function’ according to specific Problems; d) preserving the merits of BP algorithm. The simulation results increase by orders of magnitude in training -speed. This algorithm applies also some research on running mechanism of MLN.更多还原