Convergence Analysis of Batch Gradient Algorithm for Three Classes of Sigma-Pi Neural Networks
作者：Chao Zhang, Wei Wu, Yan Xiong
摘要
Sigma-Pi (Σ-Π) neural networks (SPNNs) are known to provide more powerful mapping capability than traditional feed-forward neural networks. A unified convergence analysis for the batch gradient algorithm for SPNN learning is presented, covering three classes of SPNNs: Σ-Π-Σ, Σ-Σ-Π and Σ-Π-Σ-Π. The monotonicity of the error function in the iteration is also guaranteed.
论文关键词：Convergence, Sigma-Pi-Sigma neural networks, Sigma-Sigma-Pi neural networks, Sigma-Pi-Sigma-Pi neural networks, Batch gradient algorithm, Monotonicity
论文评审过程：
论文官网地址：https://doi.org/10.1007/s11063-007-9050-0
