Automated system for detection of epileptiform patterns in EEG by using a modified RBFN classifier-Reference-Cited by-同舟云学术

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Automated system for detection of epileptiform patterns in EEG by using a modified RBFN classifier

Published:2005-08 Issue:2 Volume:29 Page:455-462
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

ACIR N

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A review of signal processing and machine learning techniques for interictal epileptiform discharge detection;Computers in Biology and Medicine;2024-01

2. Signal-Based Properties of Cyber-Physical Systems: Taxonomy and Logic-based Characterization;Journal of Systems and Software;2021-04

3. EEG autoregressive modeling analysis: A diagnostic tool for patients with epilepsy without epileptiform discharges;Clinical Neurophysiology;2020-08

4. Feature Selection Using Binary Simulated Kalman Filter for Peak Classification of EEG Signals;2018 8th International Conference on Intelligent Systems, Modelling and Simulation (ISMS);2018-05

5. Improving EEG signal peak detection using feature weight learning of a neural network with random weights for eye event-related applications;Sādhanā;2017-03-23

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