Year: 2019
Type: article
Abstract: Purkinje cell is an important neuron for the cerebellar information processing. In this work, we present an efficient implementation of a cerebellar Purkinje model using the Coordinate Rotation Digital Computer (CORDIC) algorithm and implement it on a Large-Scale Conductance-Based Spiking Neural Networks (LaCSNN) system with cost-efficient multiplier-less methods, which are more suitable for large-scale neural networks. The CORDIC-based Purkinje model has been compared with the original model in terms of the voltage activities, dynamic mechanisms, precision, and hardware resource utilization. The results show that the CORDIC-based Purkinje model can reproduce the same biological activities and dynamical mechanisms as the original model with slight deviation. In the aspect of the hardware implementation, it can use only logic resources, so it provides an efficient way for maximizing the FPGA resource utilization, thereby expanding the scale of neural networks that can be implemented on FPGAs.
Source: Frontiers in Neuroscience
Authors: Xinyu Hao, Shuangming Yang, Jiang Wang, Bin Deng, Xile Wei, Guosheng Yi
Institution: Tianjin University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,950
Awards: G3876297723, 海马癫痫样放电传播的内生电场传导机理研究
OpenAlex ID: W2980378188