2025-02-22T23:45:28-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22irk-123456789-195271%22&qt=morelikethis&rows=5
2025-02-22T23:45:28-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22irk-123456789-195271%22&qt=morelikethis&rows=5
2025-02-22T23:45:28-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-22T23:45:28-05:00 DEBUG: Deserialized SOLR response
Separation of electroencephalogram low-frequency components on the basis of the stochastic resonance effect
The paper describes the method for electroencephalogram (EEG) analysis based on the stochastic resonance (SR) effect. The numerical computation has provided the separation of low frequency components that fall within the δ-rhythm band. This is currently central in the neuropathology diagnostics, bec...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Національний науковий центр «Харківський фізико-технічний інститут» НАН України
2021
|
Series: | Вопросы атомной науки и техники |
Subjects: | |
Online Access: | http://dspace.nbuv.gov.ua/handle/123456789/195271 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The paper describes the method for electroencephalogram (EEG) analysis based on the stochastic resonance (SR) effect. The numerical computation has provided the separation of low frequency components that fall within the δ-rhythm band. This is currently central in the neuropathology diagnostics, because the presence of low frequencies in the EEG is abnormal and bears witness to the disease. For verification, the data obtained with the use of the SR effect have been compared with the computations based on the autocorrelation function (ACF) processing. The comparison has shown their good agreement. |
---|