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Design of time-pulse coded optoelectronic neuronal elements for nonlinear transformation and integration

机译:用于非线性变换和积分的时间脉冲编码光电神经元的设计

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In the paper the actuality of neurophysiologically motivated neuron arrays with flexibly programmable functions and operations with possibility to select required accuracy and type of nonlinear transformation and learning are shown. We consider neurons design and simulation results of multichannel spatio-time algebraic accumulation - integration of optical signals. Advantages for nonlinear transformation and summation -integration are shown. The offered circuits are simple and can have intellectual properties such as learning and adaptation.rnThe integrator-neuron is based on CMOS current mirrors and comparators. The performance: consumable power -100.. .500 μW, signal period- 0.1... 1ms, input optical signals power - 0.2... 20 μW; time delays - less 1 μs, the number of optical signals - 2... 10, integration time - 10... 100 of signal periods, accuracy or integration error - about 1%.rnVarious modifications of the neuron-integrators with improved performance and for different applications are considered in the paper.
机译:在本文中,显示了具有灵活可编程功能和操作的神经生理动机神经元阵列的现状,可以选择所需的精度以及非线性转换和学习的类型。我们考虑神经元的多通道时空代数累积的设计和仿真结果-光信号的集成。显示了非线性变换和求和积分的优势。所提供的电路简单,并具有学习和自适应等知识产权。rn积分器神经元基于CMOS电流镜和比较器。性能:消耗功率-100 ... 500μW,信号周期-0.1 ... 1ms,输入光信号功率-0.2 ... 20μW;时间延迟-小于1μs,光信号的数量-2 ... 10,积分时间-10 ... 100个信号周期,精度或积分误差-约1%.rn对神经元积分器的各种修改,性能得到改善本文针对不同的应用进行了考虑。

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