回归分析人工神经网络

为避免每次训练都必须随机生成样本序列的问题，提出网络动态拓扑的概念，对各种前向式网络进行统一表述；提出正、反序训练方法，并给出解的唯一性证明，同时，网络连接权在初始化时不再需要随机生成。回归分析人工神经网络有效解决了两次随机过程对训练结果造成的不利影响，在稳定性和可信性上对人工神经网络的应用提供了理论依据和技术支持。

Regression Analysis Artificial Neural Network

The concept of network dynamic topology is proposed, for a variety of pre-integrated presentation of the network to the ceremony ; make positive and negative sequence training methods, and gives proof of uniqueness of solution, avoiding each training sample must be randomly generated sequence of problems, the network connection right to randomly generated initialization is no longer needed. Regression analysis of artificial neural networks an effective solution to two stochastic processes on the training result, the adverse effects on the stability and credibility of the application of artificial neural networks provides a theoretical basis and technical support.