Name
Abstract | ||
|---|---|---|
Although the great progress in sensor and signal processing techniques have provided effective tools for quantitative research into traditional Chinese pulse diagnosis, the automatic classification of pulse waveform is remained a difficult problem. In order to address this issue, we propose a novel edit distance with real penalty-based k-nearest neighbor classifier by referring to recent progress in time series matching and KNN classifier. Taking advantage of the metric property of ERP, we develop an ERP-induced inner product operator and then embed it into difference-weighted KNN classifier. Experimental results show that the proposed classifier is more accurate than comparable pulse waveform classification approaches. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13923-9_20 | ICMB |
Keywords | Field | DocType |
erp-induced inner product operator,great progress,knn classifier,erp-based difference-weighted knn classifier,pulse waveform,traditional chinese pulse diagnosis,comparable pulse waveform classification,proposed classifier,difference-weighted knn classifier,recent progress,automatic classification,quantitative research,time series,edit distance,signal processing,inner product,k nearest neighbor | Edit distance,Pulse diagnosis,Signal processing,Pattern recognition,Computer science,Waveform,Speech recognition,Pulse (signal processing),Artificial intelligence,Margin classifier,Classifier (linguistics),Quadratic classifier | Conference |
Volume | ISSN | ISBN |
6165 | 0302-9743 | 3-642-13922-1 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongyu Zhang | 1 | 151 | 23.10 |
| Wangmeng Zuo | 2 | 3833 | 173.11 |
| Yanlai Li | 3 | 95 | 9.06 |
| Naimin Li | 4 | 147 | 21.37 |