空间传感器中基于最优细胞神经网络的智能像素阵列处理器

W. Fang, B. Sheu, H. Venus, R. Sandau
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引用次数: 0

摘要

一种具有硬件退火能力、数字可编程突触权重和多传感器并行接口的智能像素细胞神经网络正在开发中,用于先进的空间传感器应用。智能像素CNN架构是一个可编程的光电神经元的多维阵列,这些神经元与它们的局部神经元和相关的有源像素传感器局部连接。在可扩展多处理器系统的每个处理器节点中集成神经处理器,为先进小卫星的机载实时智能多传感器处理和控制任务提供数量级的计算性能增强。详细研究了智能像素CNN的工作原理、体系结构、设计与实现以及系统应用。采用2-/spl mu/m CMOS技术,实现了主动尺寸为1380 /spl mu/m/spl times/746 /spl mu/m的智能像素5/spl times/5-神经处理器阵列芯片原型,说明了VLSI实现的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart-pixel array processors based on optimal cellular neural networks for space sensor applications
A smart-pixel cellular neural network with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI implementation feasibility was illustrated by a prototype smart-pixel 5/spl times/5-neuroprocessor array chip of active dimensions 1380 /spl mu/m/spl times/746 /spl mu/m in a 2-/spl mu/m CMOS technology.
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