Selecting Statistical Characteristics of Brain Signals to Detect Epileptic Seizures using Discrete Wavelet Transform and Perceptron Neural Network
Electroencephalogram signals (EEG) have always been used in medical diagnosis. Evaluation of the statistical characteristics of EEG signals is actually the foundation of all brain signal processing methods. Since the correct prediction of disease status is of utmost importance, the goal is to use th...
Main Authors: | Rezvan Abbasi, Mansour Esmaeilpour |
---|---|
Format: | Article |
Language: | English |
Published: |
Universidad Internacional de La Rioja (UNIR)
2017-08-01
|
Series: | International Journal of Interactive Multimedia and Artificial Intelligence |
Subjects: | |
Online Access: | http://www.ijimai.org/journal/node/1496 |
Similar Items
-
River Stage Modeling by Combining Maximal Overlap Discrete Wavelet Transform, Support Vector Machines and Genetic Algorithm
by: Youngmin Seo, et al.
Published: (2017-07-01) -
NEURAL NETWORKS AS A CLASSIFICATION TOOL BIOTECHNOLOGICAL SYSTEMS (FOR EXAMPLE FLOUR PRODUCTION)
by: V. K. Bitykov, et al.
Published: (2015-07-01) -
Multilayer perceptron for face recognition
by: Ričardas Toliušis, et al.
Published: (2017-12-01) -
EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network
by: Saadullah Farooq Abbasi, et al.
Published: (2020-01-01) -
Modeling of Soil Compaction Beneath the Tractor Tire using Multilayer Perceptron Neural Networks
by: Gh Shahgholi, et al.
Published: (2018-03-01)