caa a22 4500 477034470 CHVBK 20180405111301.0 cr unu---uuuuu 170330e19960601xx s 000 0 eng 10.1007/BF00571682 doi (NATIONALLICENCE)springer-10.1007/BF00571682 A least third-order cumulants objective function [Elektronische Daten] [Chi-Tat Leung, Tommy Chow, Y. Yam] A novel Least Cumulants Method is proposed to tackle the problem of fitting to underlying function in small data sets with high noise level because higher-order statistics provide an unique feature of suppressing Gaussian noise processes of unknown spectral characteristics. The current backpropagation algorithm is actually the Least Square Method based algorithm which does not perform very well in noisy data set. Instead, the proposed method is more robust to the noise because a complete new objective function based on higher-order statistics is introduced. The proposed objective function was validated by applying to predict benchmark sunspot data and excellent results are obtained. The proposed objective function enables the network to provide a very low training error and excellent generalization property. Our results indicate that the network trained by the proposed objective function can, at most, provide 73% reduction of normalized test error in the benchmark test. Kluwer Academic Publishers, 1996 Least Cumulants Method nationallicence third-order cumulants nationallicence objective function nationallicence least cumulants based backpropagation nationallicence Leung Chi-Tat Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut Chow Tommy Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut Yam Y. Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut Neural Processing Letters Kluwer Academic Publishers 3/2(1996-06-01), 91-99 1370-4621 3:2<91 1996 3 11063 https://doi.org/10.1007/BF00571682 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00571682 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Leung Chi-Tat Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut NATIONALLICENCE 700 1- Chow Tommy Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut NATIONALLICENCE 700 1- Yam Y. Department of Electronic Engineering, City University of Hong Kong, 83, Tat Chee Road, Kowloon, Hong Kong aut NATIONALLICENCE 773 0- Neural Processing Letters Kluwer Academic Publishers 3/2(1996-06-01), 91-99 1370-4621 3:2<91 1996 3 11063 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer