Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature.

ABSTRACT:

Background

Nerve discharge is the carrier of information transmission, which can reveal the basic rules of various nerve activities. Recognition of the nerve discharge rhythm is the key to correctly understand the dynamic behavior of the nervous system. The previous methods for the nerve discharge recognition almost depended on the traditional statistical features, and the nonlinear dynamical features of the discharge activity. The artificial extraction and the empirical judgment of the features were required for the recognition. Thus, these methods suffered from subjective factors and were not conducive to the identification of a large number of discharge rhythms.

Results

The ability of automatic feature extraction along with the development of the neural network has been g

SUBMITTER: Jiang Z 

PROVIDER: S-EPMC8848584 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature