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- W2138283762 abstract "The digital spiking neuron is a wired system of shift registers and behaves like a simplified neuron model. By adjusting the wirings among the registers, the neuron can generate various spike-trains. In this paper some basic relations between the wiring pattern and spike-train characteristics are analyzed. Based on the analysis results, a hardware-oriented learning algorithm is proposed. The learning algorithm and the digital neuron are implemented by a hardware description language (HDL). It is shown that the learning algorithm enables the digital neuron to approximate various spike-trains generated by an analog spiking neuron model. In addition, some basic experimental measurements are provided by using a field programmable gate array (FPGA)." @default.
- W2138283762 created "2016-06-24" @default.
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- W2138283762 date "2008-06-01" @default.
- W2138283762 modified "2023-09-26" @default.
- W2138283762 title "A hardware-oriented learning algorithm for a digital spiking neuron" @default.
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- W2138283762 doi "https://doi.org/10.1109/ijcnn.2008.4634143" @default.
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