Title: 以FPGA晶片實現CMAC類神經網路控制器
Realization of CMAC Neural Network Controller by FPGA Chips
Authors: 何智南
Ho, Jhy-Lan
陳福川
Chen Fu-Chuang
電控工程研究所
Keywords: 小腦模組關節控制器;CMAC
Issue Date: 1996
Abstract: 由於小腦模組關節控制器(CMAC)能夠非常快速地學習非線性函數,並
進行引申 (generalization),因此在非線性系統的即時(real time)
控制上,它是一項有力且實際的工具。
在本論文中,我們將提出利用FPGA晶片實現之數位並行運算的CMAC類神經
網路。所製作的CMAC晶片是固定點(fixed point)系統,採用SIMD結構實
現CMAC並行演算法則。完成後的CMAC類神經網路包含三顆Xilinx XC4000
FPGA晶片,其中兩顆晶片執行記憶體位址的映射,另一顆晶片計算連結量
的累加及更新。這三顆FPGA晶片配合DSP處理器、SRAM及一些週邊電路構
成一完整的測試系統。我們測試了CMAC的學習特性及其在非線性控制上的
效能。
The Cerebellar Model Articulation Controller(CMAC) is capable
of learning nonlinear functions extremely quickly due to its
generalizing capability,so itis a powerful and practical tool
for real time control.In this studywe present a realization of
the CMAC neural network by FPGA chips.We employ the fixed point
system and adopt the SIMD architecture to implement the CMAC
parallel algorithm.Hardware design is accomplished by three
Xilinx XC4000 FPGA chips.Two FPGA chips carry out address
mapping and the other chip does weight accumulation and weight
modification.The test system includes FPGA chips,DSP processor,
SRAM and some peripheral circuits.We show the performance of
the CMAC chips in learning and in nonlinear control.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT850327005
http://hdl.handle.net/11536/61656
Appears in Collections:Thesis