计算机工程2011，Vol.37Issue(20)：211-212,215,3.DOI:10.3969/j.issn.1000-3428.2011.20.073
基于分段线性插值的过程神经网络训练
Process Neural Network Training Based on Piecewise Linear Interpolation
摘要
Abstract
Process Neural Network(PNN) can only receive time-varying continuous functions, can not receive discrete samples. To solve this problem, a training algorithm of PNN based on piecewise linear interpolation function is proposed. The discrete data of both sample functions and weight functions are transformed to piecewise linear functions, and then the integrals of product of two linear functions at a given sampling interval are computed. As a result of aggregation, these integrals are submitted to process neurons of PNN hide layer. The networks output is obtained. Experimental results show the availability of the proposed method.关键词
过程神经元/过程神经网络/线性插值函数/神经网络训练Key words
process neuron/ Process Neural Network(PNN)/ linear interpolation function/ neural network training分类
信息技术与安全科学引用本文复制引用
肖红,曹茂俊,李盼池,王海英..基于分段线性插值的过程神经网络训练[J].计算机工程,2011,37(20):211-212,215,3.基金项目
国家自然科学基金资助项目(61170132) （61170132）
中国博士后科学基金特别资助项目(201003405) （201003405）
中国博士后科学基金资助项目(20090460864) （20090460864）
黑龙江省博士后科学基金资助项目(LBH-Z09289) （LBH-Z09289）
黑龙江省教育厅科学技术研究基金资助项目(11551015,11551017) （11551015,11551017）
