DocumentCode :
336172
Title :
Signal compression by piecewise linear non-interpolating approximation
Author :
Nygaard, Ranveig ; Husoy, J.H. ; Haugland, Dag ; Aase, Sven Ole
Author_Institution :
Dept. of Electr. & Comput. Technol., Stavanger Coll., Norway
Volume :
3
fYear :
1999
fDate :
15-19 Mar 1999
Firstpage :
1273
Abstract :
We present a signal compression scheme based on coding linear segments approximating the signal. Although the approach is useful for many types of signals, we focus in this paper on compression of electrocardiogram (EGG) signals. The ECG signal compression has traditionally been tackled by heuristic approaches. However, it has been demonstrated that exact optimization algorithms outclass these heuristic approaches by a wide margin with respect to the reconstruction error. The exact optimization algorithm extracts signal samples from the original signal by formulating the sample selection problem as a graph theory problem. Thus known optimization theory can be applied in order to yield optimal compression. This paper generalizes the exact optimization scheme by removing the interpolation restriction when applying piecewise linear approximation. This guarantees a lower reconstruction error with respect to the number of extracted signal samples. The method shows superior performance compared to traditional ECG compression methods
Keywords :
approximation theory; bioelectric potentials; data compression; electrocardiography; encoding; graph theory; medical signal processing; optimisation; piecewise linear techniques; signal reconstruction; ECG signal compression; electrocardiogram; exact optimization algorithms; graph theory; heuristic approaches; optimal compression; optimization theory; performance; piecewise linear noninterpolating approximation; reconstruction error; sample selection problem; signal coding; signal samples; Data mining; Decoding; Electrocardiography; Graph theory; Interpolation; Linear approximation; Mathematical model; Piecewise linear approximation; Piecewise linear techniques; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
ISSN :
1520-6149
Print_ISBN :
0-7803-5041-3
Type :
conf
DOI :
10.1109/ICASSP.1999.756211
Filename :
756211
Link To Document :
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