Clustering Algorithm Analysis and FPGA Implementation of Neural Electrical Signal

The biological signals collected by the multi-electrode array are contaminated by heavy noise signals. How to quickly classify the original action potential from the measured noisy signals accurately is the basis of researches in the field of neuroscience. In this paper, we analyze the characteristics and shortcomings of Wave-clus sorting algorithm, and present a novel sorting algorithm to solve the classification problem of neuronal action potentials. Besides, a novel method of FPGA implementation is introduced for the clustering algorithm. The method and simulation results of estimating the waveform function model are given. The prediction electrode data and the algorithm of the residual function module are set up and the error analysis is carried out. The simulation results show that the proposed method has a satisfied performance.