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Analog VLSI CMOS implementation of beta neuron in a low power low voltage environment

机译:模拟VLSI CMOS在低功耗低压环境中的β神经元的实现

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A new CMOS analog programmable beta function for Beta Basis Function Neural Networks is proposed. Based on current mode operations and using devices operating in the subthreshold region, low power low voltage operations are carried out. The supply voltage is 1.3V and the quiescent power consumption is 4??W. The proposed circuit makes use of the weak inversion MOS model. It carried out a compact implementation of a current mode logarithmic converter, a one quadrant programmable multiplier and a current exponentiator. The beta exponents of the design are tuneable by means of control sources. Design modularity concerns also the maximum beta function value. Pspice simulations were done for a 0,35??m CMOS process of AMS. Correct operations of the different blocks were observed. The relative error between theory and simulations of the beta function is less than 2%.
机译:提出了一种新的CMOS模拟可编程Beta函数,用于测试型函数神经网络。 基于电流模式操作和使用在亚阈值区域中操作的设备,执行低功耗低电压操作。 电源电压为1.3V,静态功耗为4 ?? w。 所提出的电路利用弱反转MOS模型。 它执行了电流模式对数转换器的紧凑型实现,一个象限可编程乘法器和当前的指数引擎。 设计的β指数通过控制来源进行可调。 设计模块化也关注最大Beta函数值。 PSPICE模拟是为AMS的0.35米CMOS过程完成的。 观察到不同块的正确操作。 Beta函数的理论和模拟之间的相对误差小于2%。

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