Identification of resting and active state EEG features of Alzheimer's disease using discrete wavelet transform.
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Brain MR Image Classification for Alzheimer's Disease Diagnosis Based on Multifeature Fusion.Stochastic non-linear oscillator models of EEG: the Alzheimer's disease case.Exploration of EEG features of Alzheimer's disease using continuous wavelet transform.Analysis of long range dependence in the EEG signals of Alzheimer patients.Extracting Salient Features for EEG-based Diagnosis of Alzheimer's Disease Using Support Vector Machine ClassifierSystematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression AssessmentDenoising Method Based on Sparse Representation for WFT Signal
P2860
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P2860
Identification of resting and active state EEG features of Alzheimer's disease using discrete wavelet transform.
description
2013 nî lūn-bûn
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2013年論文
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name
Identification of resting and ...... ng discrete wavelet transform.
@en
Identification of resting and ...... ng discrete wavelet transform.
@nl
type
label
Identification of resting and ...... ng discrete wavelet transform.
@en
Identification of resting and ...... ng discrete wavelet transform.
@nl
prefLabel
Identification of resting and ...... ng discrete wavelet transform.
@en
Identification of resting and ...... ng discrete wavelet transform.
@nl
P2093
P2860
P1476
Identification of resting and ...... ng discrete wavelet transform.
@en
P2093
Adam J Simon
Ajay Verma
Allan Bernstein
David M Devilbiss
Hashem Ashrafiuon
Parham Ghorbanian
Terry Hess
P2860
P2888
P304
P356
10.1007/S10439-013-0795-5
P577
2013-03-28T00:00:00Z
P5875
P6179
1046704244