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首页> 外文期刊>IEEE Transactions on Neural Networks >A communication architecture tailored for analog VLSI artificial neural networks: intrinsic performance and limitations
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A communication architecture tailored for analog VLSI artificial neural networks: intrinsic performance and limitations

机译:专为模拟VLSI人工神经网络量身定制的通信体系结构:固有性能和局限性

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摘要

An architecture for interchip communication among analog VLSI neural networks is proposed. Activity is encoded in a neuron's pulse emission frequency. Information is transmitted through the non-arbitered, asynchronous access of pulses to a common bus. The impact of collisions when the bus is accessed by more than one user is investigated. The information-carrying capability is assessed and the trade-off between accuracy of the transmitted information and attainable dynamic range is brought out in terms of simple global parameters that characterize the application. It is found that the proposed architecture is well suited for the kind of communication requirements associated to neural computation systems. A coding scheme aimed at pushing the system towards its theoretical performance is also presented and evaluated.
机译:提出了一种在模拟VLSI神经网络之间进行芯片间通信的架构。活动被编码为神经元的脉冲发射频率。信息通过对脉冲的非仲裁,异步访问到公共总线进行传输。研究了多个用户访问总线时冲突的影响。评估信息的承载能力,并根据表征应用程序的简单全局参数,在传输信息的准确性与可达到的动态范围之间进行权衡。发现所提出的体系结构非常适合与神经计算系统相关的通信要求。还提出并评估了旨在将系统推向理论性能的编码方案。

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