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The application of wavelet and feature vectors to ECG signals
Mirjam Jonkman
, A Matsuyama
Research output
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Contribution to journal
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Article
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peer-review
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Dive into the research topics of 'The application of wavelet and feature vectors to ECG signals'. Together they form a unique fingerprint.
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Computer Science
Application
100%
Feature Vector
100%
Entropy
25%
Domains
25%
Classification
25%
Frequency Information
25%
Feature Extraction
12%
Intents
12%
Wavelet Transforms
12%
Time Information
12%
Copyright
12%
Wavelet Decomposition
12%
Pathological Condition
12%
Biochemistry, Genetics and Molecular Biology
Electrocardiogram
100%
Time
50%
Energy
25%
Recording
25%
Entropy
25%
Classification
25%
Wavelet Analysis
25%
Electric Potential
12%
Extract
12%
Decomposition
12%
Feature Extraction
12%
Fourier Analysis
12%
Nursing and Health Professions
Electrocardiogram
100%
Time
50%
Recording
25%
Classification
25%
Analysis
25%
Procedures
12%
Physician
12%
Electric Potential
12%
Diagnosis
12%
Biological Product
12%
Extract
12%
Chemistry
Application
100%
Time
50%
Energy
25%
Entropy
25%
Molecular Cluster
12%
Decomposition
12%
Economics, Econometrics and Finance
Information
25%