non-differential function meaning in English

不可微分函数

The bp algorithm is kind of algorithm which is in use widely in multilayer neural network , because the bp algorithm is a kind of gradient descended searching algorithm in essence , it has weaknesses such as inefficient , slow convergent speed and easy getting into local minimum , insurable to find global extreme value point for multi - modal and non - differential function in larger searching zone , which restrict neural network ’ s application in all fields . so from the principle , analysis the reasons of bp algorithm to be dropped in local minimization and propose a global optima strategy . the global optima strategy is discussed from two aspects , one of improved strategy based on model , and another based on algorithm
Bp算法是多层前向神经网络中应用最为广泛的一种算法，但是由于bp算法实质上是一种基于梯度下降的搜索算法，因此它存在着算法效率较低、收敛速度慢、易于陷入局部极小值等现状；对于较大的搜索空间、多峰值和不可微函数常常不能搜索到全局极小点，这些制约了bp网络在各个领域中的应用，本文从bp网络的工作原理出发，分析产生局部极小的原因，提出了对bp网络全局优化的改进策略。