【摘要】 提出了FCMAC(Fuzzy CMAC)的一种基于FPGA的硬件实现方法,与其他FPGA实现神经网络相比,它包含了可以用于在线学习的权学习算法。首先分析了FCMAC的模型结构及相应的硬件模块,然后基于VHDL语言实现了各模块的功能描述,最后将FPGA实现的FCMAC用于控制应用,并对控制器进行测试。实验结果表明,FCMAC的实现方案是可行的,控制器运算速度快、精度高,且具有较强的抗干扰性,是实现IP控制模块或单片智能控制的一种新的有效途径。更多还原

【Abstract】 An FPGA implementation structure of a FCMAC(Fuzzy CMAC) was proposed.Compared with other neural networks implemented by FPGA,it contains the learning algorithm that can be employed to realize the on-line learning.First,the model of FCMAC was given and the relevant hardware modules were analyzed.Second,these hardware modules were implemented with VHDL.At last,the implemented FCMAC was used for control,and the corresponding controller was tested.The experimental results indicate that this method for hardware implementation of FCMAC is feasible,and the controller has high computing speed,high precision and better ability of anti-interfere.It is a new and efficient method to implement IP control module or intelligent control based on a single chip.更多还原