一种神经网络稳健估计方法的推广性研究
GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS
-
摘要: 本文根据统计学的稳健性原理,将柯西(Cauchy)函数作为新的神经网络目标函数。在网络参数相同的前提下,利用传统的均方目标函数和新的柯西目标函数对BP网络分别进行训练后,加入小噪声及异常值(Outliers)干扰对该网络进行测试。结果表明,具有稳健性目标函数的网络不但有更快的收敛速度,而且对异常值有更好的抵抗能力。Abstract: In this paper, the Cauchy function is taken as a new target function of neural network accordings to the robustness theorem of statistics. Under the same network parameter conditions the BP net is trained using both mean squresand Cauchy target function firstly, then the net is tested by data sets including small Gaussian noises and outliers separately. Simulation results indicate that the network has both faster convergence speed and better performance against outliers after learning with robust target function.
-
Huber P J. Robust estimation of a location parameter[J].The Annals of Mathematical Statistics.1964, 35:73-101[2]Andrews D A. Robust method for mutiple linear regression[J].Technometrics.1974, 16:523-531[3]Liano K. Robust error measure for supervised neural network learning with outliers. IEEE Trans. on Neural Networks, 1996, NN-7(1): 244-250.[4]Chen D S, Jain R C. A robust back propagation learning algorithm for function appoximation. IEEE Trans. on Neural Networks, 1994, NN-5(3): 467-469.[5]Oja E, Wang L. Robust fitting by nonlinear neural units[J].Neural Networks.1996, 9(3):435-444[6]Humpert B K. Improving back propagation with a new error function. Neural Nerworks, 1994, 7(R)- 1101-1149.[7]陈希孺, 王松桂. 近代实用回归分析. 南宁:广西人民出版社, 1984: 301-321.[8]廖晓峰, 刘光远, 虞厥邦.几种误差估计器的稳健BP:理论与算法.信号处理,1997, 13(3): 235-240. -
计量
- 文章访问数: 2173
- HTML全文浏览量: 102
- PDF下载量: 405
- 被引次数: 0
下载:
