Terminal attractor based back propagation learning for feedforward neural networks

摘要

In this paper, the terminal attractor based back propagation learning algorithms for feedforward neural networks are examined. Through a rigorous mathematical analysis, a condition to guarantee the convergence of the algorithms is given. A simulation study is presented to demonstrate the effectiveness of the analysis.