基于细胞神经网络的多媒体应用传感器/处理器集成

B. Sheu, K. Cho, W. C. Young
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引用次数: 8

摘要

随着先进计算体系结构和阵列处理技术的研究和发展取得重大进展,紧凑、高计算能力的系统成为可能。采用0.5 mm HP CMOS技术开发了一种可扩展的图像传感器阵列处理器,该处理器具有帧存储缓冲和用于最近邻交互的细胞神经网络(CNN)。采用电流模技术,利用紧凑的混合信号电路元件构建了具有模拟可编程权重的CNN。电流模式方案可根据电源电压适当缩放,支持低电压、低功耗运行。可在原型中加入可变增益神经元电路的设计,利用硬件退火实现最优解能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of sensor/processor under cellular neural networks paradigm for multimedia applications
Compact, high computing power systems become feasible with significant progress in the research and development of advanced computing architecture and array processing. A scalable image sensor array processor with frame memory buffer and cellular neural network (CNN) for nearest neighbor interaction has been developed in a 0.5 mm HP CMOS technology. A CNN with analog programmable weights was constructed with compact mixed-signal circuit components in the current-mode technique. The low voltage, low power operation is supported with the current mode scheme which scales appropriately with the supply voltage. Design of a variable gain neuron circuit can be incorporated into the prototype to realize the optimal solution capability using hardware annealing.
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