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EVENT RECOGNITION HARDWARE BASED ON NEURON MOS SOFT-COMPUTING CIRCUITS

机译:基于NEURON MOS软电路的事件识别硬件

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Neuron MOS transistor (neuMOS or vMOS) mimicking the fundamental behavior of neurons at a primitive device level allows the implementation of intelligent functions directly on the integrated circuit hardware. Based on the vMOS technology a real-time event recognition system has been developed. A neuron MOS association processor searches for the event in the past memory having the maximum similarity to the current event presented to the system. This is based on Manhattan-distance calculation and the minimum distance search by a winner-take-all (WTA) circuitry. The computation is carried out directly on the hardware in a fully parallel architecture. A unique floating-gate analog EEPROM technology has been developed to build a vast memory system storing past events in multivalued vectors. Test circuits of key subsystems were fabricated by a double-polysilicon CMOS process and their operation was verified by measurements as well as by simulation. The vMOS circuit operation is characterized by analog computation directly conducted on an electrically floating node which is immediately followed by the thresholding action of a transistor to yield a binary decision. vMOS circuits would provide an opportunity for a very flexible soft computing scheme, while preserving the rigorous nature of digital processing.
机译:在原始设备级别上模仿神经元基本行为的神经元MOS晶体管(neuMOS或vMOS)可以直接在集成电路硬件上实现智能功能。基于vMOS技术,开发了实时事件识别系统。神经元MOS关联处理器在过去的内存中搜索与呈现给系统的当前事件具有最大相似度的事件。这是基于曼哈顿距离计算和赢家通吃(WTA)电路进行的最小距离搜索。计算是在完全并行的体系结构中直接在硬件上执行的。已经开发出独特的浮栅模拟EEPROM技术,以构建庞大的存储系统,将过去的事件存储在多值向量中。关键子系统的测试电路是通过双多晶硅CMOS工艺制造的,并通过测量和仿真验证了它们的操作。 vMOS电路操作的特征在于,直接在电浮动节点上进行模拟计算,然后立即进行晶体管的阈值作用以产生二进制判决。 vMOS电路将为非常灵活的软计算方案提供机会,同时保留数字处理的严格性质。

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