A VLSI Spiking Feedback Neural Network with Negative Thresholding and Its Application to Associative Memory(<Special Section>Novel Device Architectures and System Integration Technologies)
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概要
- 論文の詳細を見る
An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.
- 社団法人電子情報通信学会の論文
- 2006-11-01
著者
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Iwata Atsushi
Graduate School Of Advanced Sciences Of Matter Hiroshima University
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Morie Takashi
Graduate School Of Life Science And Systems Engineering Kyushu Institute Of Technology
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Sasaki Kan'ya
Graduate School Of Advanced Sciences Of Matter Hiroshima University
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