计算机技术与发展2016，Vol.26Issue(10)：50-54,5.DOI:10.3969/j.issn.1673-629X.2016.10.011
一类乘性有理样条权函数神经网络灵敏度分析
Sensitivity Analysis of Neural Network with Rational Spline Weight Functions Using Multiplicative Neurons
摘要
Abstract
The neural network with spline weight function is a new kind of neural network,which overcomes many problems such as slow convergence speed,sensitive to initial value and local minima. It is widely concerned because of its accurate learning approach to given patterns,simple network topology,fast training speed and so on. Based on the advantage of neural network with spline weight function, the sensitivity of neural network with cubic numerator and linear denominator of rational spline weight functions using multiplicative neu-rons is discussed,and the accuracy of analytical results is verified by simulation. Both the theoretical analysis and simulation results show that when the disturbance is in a certain range,the sensitivity of this kind of spline weight function neural network is very stable,and is featured with strong noise resistance.关键词
样条权函数/样条插值/神经网络/灵敏度分析Key words
spline weight function/spline interpolation/neural network/sensitivity analysis分类
信息技术与安全科学引用本文复制引用
张代远,王雷雷..一类乘性有理样条权函数神经网络灵敏度分析[J].计算机技术与发展,2016,26(10):50-54,5.基金项目
江苏高校优势学科建设工程资助项目(yx002001) （yx002001）
