一种CMAC超闭球结构及其学习算法
CMAC with Hyperball Structure and its Learning Algorithm
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摘要: 提出了一种CMAC(Cerebellar Model Articulatlon Controller)输入空间超闭球量化 方法.基于超闭球上模糊基函数的信息存储与恢复策略,还给出了快速收敛的学习算法.通过 非线性动态系统建模仿真研究,结果表明CMAC具有很强的学习记忆和泛化能力.Abstract: This paper presents the CMAC(cerebellar model articulation controller), which can guarantee the input space by hyperballs. Based on the fuzzy basis functions defined on the hyperballs, information is stored and retrieved. A fast convergent learning algorithm is also given. Simulations for the CMAC used in nonlinear dynamic system modeling are performed to demonstrate its powerful associative memory and generalization performance.
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Key words:
- CMAC /
- associative memory /
- learning algorithms
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