TY - GEN
T1 - Minimum classification error using time-frequency analysis
AU - Breakenridge, C.
AU - Mesbah, M.
N1 - Publisher Copyright:
© 2003 IEEE.
PY - 2003
Y1 - 2003
N2 - For certain classes of signals, such as time varying signals, classical classification algorithms are not suitable. Hence, time-frequency based techniques are employed for classification of these types of signals. In this paper we propose data-driven time frequency representations kernel optimization, that leads to the minimum classification error (MCE) for nonstationary signal classification. Our central issue is to determine the optimal kernel parameters and best distance measure to achieve the MCE performance measure. The minimum classification error achievable using optimized kernels is investigated for two types of nonstationary signals; namely simulated chirp signals and real-life newborn EEG signals. For the EEG signals a classification error as low as 4.6% was achieved.
AB - For certain classes of signals, such as time varying signals, classical classification algorithms are not suitable. Hence, time-frequency based techniques are employed for classification of these types of signals. In this paper we propose data-driven time frequency representations kernel optimization, that leads to the minimum classification error (MCE) for nonstationary signal classification. Our central issue is to determine the optimal kernel parameters and best distance measure to achieve the MCE performance measure. The minimum classification error achievable using optimized kernels is investigated for two types of nonstationary signals; namely simulated chirp signals and real-life newborn EEG signals. For the EEG signals a classification error as low as 4.6% was achieved.
KW - Algorithm design and analysis
KW - Chirp
KW - Electroencephalography
KW - Kernel
KW - Optimization methods
KW - Pediatrics
KW - Signal analysis
KW - Signal processing algorithms
KW - Testing
KW - Time frequency analysis
UR - http://www.scopus.com/inward/record.url?scp=77950292140&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950292140&partnerID=8YFLogxK
U2 - 10.1109/ISSPIT.2003.1341221
DO - 10.1109/ISSPIT.2003.1341221
M3 - Conference contribution
AN - SCOPUS:77950292140
T3 - Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
SP - 717
EP - 720
BT - Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
Y2 - 14 December 2003 through 17 December 2003
ER -