Primitive coding of structural ECG features
| Autor: | Antti Koski |
|---|---|
| Rok vydání: | 1996 |
| Předmět: |
Signal processing
Learning vector quantization business.industry Speech recognition Quantization (signal processing) Codebook Pattern recognition Syntactic pattern recognition ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Test set Signal Processing Computer Vision and Pattern Recognition Artificial intelligence Ecg signal business Software Mathematics Coding (social sciences) |
| Zdroj: | Pattern Recognition Letters. 17:1215-1222 |
| ISSN: | 0167-8655 |
| DOI: | 10.1016/0167-8655(96)00079-7 |
| Popis: | In this paper, a hybrid of self-organizing feature map and learning vector quantization and a rule base classification for the extraction of structural primitives of ECG signals is presented. Structural primitives are the elementary building blocks of an ECG signal and they are used in the syntactic recognition and analysis of the signal. The analysis based on the coding by the codebook vectors and slope rules was as successful as the analysis of the manually labelled test set. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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