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As for nervous diseases study, building specific models tends to be really hard but significant. This paper introduces a novel method for neuron system identification using nonlinear auto-regressive Volterra (NARV) model based on the field programmable gate arrays (FPGA). We select HH model as a “black-box” system requiring identification, and obtain input and output data. A NARV model built on the...
The small-world network plays a vital role in brain function investigation and complex network study. Multi-FPGA design for the spiking neural network remains some challenges in hardware simulation and application. In this paper, a novel multi-FPGA design is proposed to implement a modular small-world network which can ensure a high computational speed and a high calculation accuracy. Time-division...
Multilayer feedforward networks are related to functional groups of neurons where information is transmitted from one group to the next. It is a generic framework to characterize the properties of spiking activities in propagation. In this paper, we designed a novelty structure of feedforward network on FPGA to propagate the synchronous spiking activities. The experiment results demonstrate that the...
Based on the dynamics of neurons, we use the FPGA to realize Morris-Lecar (ML) model, and to achieve dynamic analysis such as bifurcation.etc in this paper, obtaining the corresponding firing patterns; then we use the FPGA to achieve the ML neuron network which is connected by chemical synapse, and analyze the affection of parameters on the neural network dynamic characteristics; At the same time,...
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