Title :
The learning convergence of CMAC in frequency domain and a modified algorithm
Author :
Lei, Zhang ; Qi-xin, Cao
Author_Institution :
Res. Inst. of Robot., Shanghai Jiao Tong Univ., Shanghai
Abstract :
The analysis on the learning convergence of CMAC in frequency domain is firstly extended to a more general case where the training samples are evenly distributed in the quantitative range and the learning rate is other than one. The convergence condition is presented and the influence of the learning rate beta on the convergence range is analyzed. If 0< beta<1, CMAC is convergent in the whole frequency domain. If 1lesbeta<2, the convergence of CMAC will become more unstable with beta becoming larger. To overcome this problem, a modified algorithm is proposed and simulation results prove the stability of CMAC can be improved significantly.
Keywords :
cerebellar model arithmetic computers; frequency-domain analysis; learning (artificial intelligence); CMAC; frequency domain; learning convergence; Algorithm design and analysis; Convergence; Frequency domain analysis; Intelligent control; Intelligent robots; Robotics and automation; Stability; CMAC; frequency domain; learning convergence;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4592801
