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METHODS AND APPARATUS FOR SPIKING NEURAL NETWORK COMPUTING BASED ON A MULTI-LAYER KERNEL ARCHITECTURE

机译:基于多层核体系结构的神经网络计算方法和装置

摘要

Methods and apparatus for spiking neural network computing based on e.g., a multi-layer kernel architecture, shared dendritic encoding, and/or thresholding of accumulated spiking signals. In one exemplary embodiment, a multi-layer mixed-signal kernel is disclosed that uses different characteristics of its constituent stages to perform neuromorphic computing. Specifically, analog domain processing inexpensively provides diversity, speed, and efficiency, whereas digital domain processing enables a variety of complex logical manipulations (e.g., digital noise rejection, error correction, arithmetic manipulations, etc.). Isolating different processing techniques into different stages between the layers of a multi-layer kernel results in substantial operational efficiencies.
机译:用于基于例如多层内核架构,共享树状编码和/或累积尖峰信号的阈值的尖峰神经网络计算的方法和装置。在一个示例性实施例中,公开了一种多层混合信号内核,其使用其组成阶段的不同特性来执行神经形态计算。具体地,模拟域处理廉价地提供了多样性,速度和效率,而数字域处理使得能够进行多种复杂的逻辑操作(例如,数字噪声抑制,纠错,算术操作等)。将不同的处理技术隔离到多层内核的各层之间的不同阶段中,可以提高运行效率。

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