کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
407577 | 678158 | 2013 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: KCMAC-BYY: Kernel CMAC using Bayesian Ying–Yang learning KCMAC-BYY: Kernel CMAC using Bayesian Ying–Yang learning](/preview/png/407577.png)
The Cerebellar Model Articulation Controller (CMAC) possesses attractive properties of fast learning and simple computation. In application, the size of its association vector is always reduced to economize the memory requirement, greatly constraining its modeling capability. The kernel CMAC (KMAC), which provides an interpretation for the traditional CMAC from the kernel viewpoint, not only strengthens the modeling capability without increasing its complexity, but reinforces its generalization with the help of a regularization term. However, the KCMAC suffers from the problem of selecting its hyperparameter. In this paper, the Bayesian Ying–Yang (BYY) learning theory is incorporated into KCMAC, referred to as KCMAC-BYY, to optimize the hyperparameter. The proposed KCMAC-BYY achieves the systematic tuning of the hyperparameter, further improving the performance in modeling and generalization. The experimental results on some benchmark datasets show the prior performance of the proposed KCMAC-BYY to the existing representative techniques.
Journal: Neurocomputing - Volume 101, 4 February 2013, Pages 24–31