Using $\cal SEEK$ for Multi-Channel Pattern Recognition
| dc.contributor.author | Birman, Kenneth P. | en_US |
| dc.date.accessioned | 2007-04-23T16:46:11Z | |
| dc.date.available | 2007-04-23T16:46:11Z | |
| dc.date.issued | 1982-10 | en_US |
| dc.description.abstract | Our work on computerized analysis of the 2-channel, 24-hr electrocardiogram has resulted in the development of multi-channel signal processing systems that learn by observation. In this paper a new tool for implementing such algorithms is described: the pattern recognition language $\cal SEEK$. Programs written in $\cal SEEK$ build a knowledge base containing tree-like data structures, each of which stores acquired information about a particular multi-channel waveform. Input data is interpreted by performing an efficient parallel evaluation of the structures in the knowledge base. Our work is applicable to a wide variety of pattern recognition problems that arise in medical signal processing. The approach is illustrated with examples drawn from ECG analysis. | en_US |
| dc.format.extent | 3054084 bytes | |
| dc.format.extent | 707657 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.format.mimetype | application/postscript | |
| dc.identifier.citation | http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR82-529 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1813/6368 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Cornell University | en_US |
| dc.subject | computer science | en_US |
| dc.subject | technical report | en_US |
| dc.title | Using $\cal SEEK$ for Multi-Channel Pattern Recognition | en_US |
| dc.type | technical report | en_US |