Hikawa H
Dept. of Comput. Sci. and Intelligent Syst., Oita Univ., Japan.
IEEE Trans Neural Netw. 2003;14(5):1028-37. doi: 10.1109/TNN.2003.816058.
This paper proposes a new type of digital pulse-mode neuron that employs piecewise-linear function as its activation function. The neuron is implemented on field programmable gate array (FPGA) and tested by experiments. As well as theoretical analysis, the experimental results show that the piecewise-linear function of the proposed neuron is programmable and robust against the change in the number of input signals. To demonstrate the effect of piecewise-linear activation function, pulse-mode multilayer neural network with on-chip learning is implemented on FPGA with the proposed neuron, and its learning performance is verified by experiments. By approximating the sigmoid function by the piecewise-linear function, the convergence rate of the learning and generalization capability are improved.
本文提出了一种新型数字脉冲模式神经元,其采用分段线性函数作为激活函数。该神经元在现场可编程门阵列(FPGA)上实现并通过实验进行测试。与理论分析一样,实验结果表明,所提出神经元的分段线性函数是可编程的,并且对输入信号数量的变化具有鲁棒性。为了证明分段线性激活函数的效果,使用所提出的神经元在FPGA上实现了具有片上学习功能的脉冲模式多层神经网络,并通过实验验证了其学习性能。通过用分段线性函数逼近Sigmoid函数,提高了学习的收敛速度和泛化能力。