Classification of gene expression data using Spiking Wavelet Radial Basis Neural Network

作者：

Highlights：

• Proposed spiking function is for the non linear integrate fire neuron model (NLIF).

• The proposed spiking function in NLIF generates biologically plausible spikes.

• Derived inter spike interval is used in the Wavelet Radial Basis Neural Network.

• SWRNN is used for the classification of benchmark gene expression datasets.

• SWRNN is superior to WRNN in terms of classification accuracy and time.

摘要

•Proposed spiking function is for the non linear integrate fire neuron model (NLIF).•The proposed spiking function in NLIF generates biologically plausible spikes.•Derived inter spike interval is used in the Wavelet Radial Basis Neural Network.•SWRNN is used for the classification of benchmark gene expression datasets.•SWRNN is superior to WRNN in terms of classification accuracy and time.

论文关键词：Radial Basis Neural Network,Wavelet Radial Basis Neural Network,Spiking neuron model

论文评审过程：Available online 29 August 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.08.030