The learning algorithm is a process of chaos optimization, which can make the network avoid the local minima problem and false saturation phenomenon. 网络的学习过程是一种混沌优化算法，可有效避免普通神经网络的局部极值和假饱和现象的发生。
Based on the congruence non-repetition and ergodicity of chaos, the method will avoid the local optimal solution and find satisfactory globe optimal solution. 由于混沌优化算法的叠代具有不重复性和遍历性，因此该算法可以避免陷入局部最优点而获得全局最优。
