一种改进的BP算法及其在模式识别中的应用

An Improved BP Algorithm and Applied in the Pattern Recognition

针对前馈神经网络中传统BP算法的局限性,给出了一种改进的BP算法,选取了一种新的误差函数,并对其参数进行了动态自适应调整。通过比较,改进的BP算法收敛特性明显优于传统的BP算法。实践证明,将上述算法应用于对工业零件的识别当中,可有效提高识别速度和识别正确率约17%。

This paper presented an improved BP algorithm based on the limitations of traditional BP algorithm in the feedforward neural network, adopted a sort of new error function, and adjusted its parameters dynamically and self-adaptedly. By means of comparison, the convergence character of improved BP algorithm is obviously better than the traditional ones. When the algorithm is applied in the identification of industrial parts, in practice the speed and accuracy of identification will be improved effectively.