张黎黎, 李志军. 可编程神经元sigmoid函数及其导数发生器的实现[J]. 云南大学学报(自然科学版), 2016, 38(1): 44-53. doi: 10.7540/j.ynu.20150294
引用本文: 张黎黎, 李志军. 可编程神经元sigmoid函数及其导数发生器的实现[J]. 云南大学学报(自然科学版), 2016, 38(1): 44-53. doi: 10.7540/j.ynu.20150294
ZHANG Li-li, LI Zhi-jun. Realizations of the generator of neuron sigmoid function and its derivative with continuously programmable characteristics[J]. Journal of Yunnan University: Natural Sciences Edition, 2016, 38(1): 44-53. DOI: 10.7540/j.ynu.20150294
Citation: ZHANG Li-li, LI Zhi-jun. Realizations of the generator of neuron sigmoid function and its derivative with continuously programmable characteristics[J]. Journal of Yunnan University: Natural Sciences Edition, 2016, 38(1): 44-53. DOI: 10.7540/j.ynu.20150294

可编程神经元sigmoid函数及其导数发生器的实现

Realizations of the generator of neuron sigmoid function and its derivative with continuously programmable characteristics

  • 摘要: 基于跨导线性原理,提出了一种能实现单极性和双极性sigmoid激活函数及其导数的可编程发生器.该发生器结构简单,仅由一个跨导线性环和2个差分跨导电路构成.该电路可实现单极性和双极性sigmoid函数输出,通过改变外部偏置电流和电压调节激活函数的幅值、增益因子和阈值,并可以选择电流或电压输出,因而可广泛应用于各种电流模式或者电压模式神经网络中.采用TSMC 0.35μm CMOS标准集成工艺对电路进行PSPICE仿真测试,结果表明该电路产生的激活函数及其导数与理想函数拟合度好,并具有适用范围宽、编程性好的优点.

     

    Abstract: A programmable generator is proposed that can achieve the unipolar and the ambipolar sigmoid functions with its derivatives.The proposed generator is a simple structure,composed of a translinear loop circuit and two differential transconductance circuits.The circuit can realize the unipolar and the ambipolar sigmoid functions output,adjust the amplitude,the gain factor and the threshold of the generated function through changing external bias current or voltage,and the current or voltage can be selected as output signal,thus,the generator has been widely used in various current-mode or voltage-mode neural networks.PSPICE simulation test is employed with TSMC 0.35μm CMOS standard technology to verify the circuit validity.The results show a good fitting degree between the generated functions with its derivatives and ideal functions,and have the advantages of wide application range and good programmability for the proposed circuit.

     

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