TY - GEN
T1 - Survival kernel with application to kernel adaptive filtering
AU - Chen, Badong
AU - Zheng, Nanning
AU - Principe, Jose C.
PY - 2013
Y1 - 2013
N2 - In this paper, we define a new Mercer kernel, namely survival kernel, which is closely related to our recently proposed survival information potential (SIP). The new kernel function is parameter free, simple in calculation, and strictly positive-definite (SPD) over Rm+, hence it has potential utility in machine learning especially in online kernel learning. In this work we apply the survival kernel to kernel adaptive filtering, in particular the kernel least mean square (KLMS) algorithm. Simulation results show that KLMS with survival kernel may achieve satisfactory performance with little computational time and without the choice of free parameters.
AB - In this paper, we define a new Mercer kernel, namely survival kernel, which is closely related to our recently proposed survival information potential (SIP). The new kernel function is parameter free, simple in calculation, and strictly positive-definite (SPD) over Rm+, hence it has potential utility in machine learning especially in online kernel learning. In this work we apply the survival kernel to kernel adaptive filtering, in particular the kernel least mean square (KLMS) algorithm. Simulation results show that KLMS with survival kernel may achieve satisfactory performance with little computational time and without the choice of free parameters.
KW - KLMS
KW - Survival kernel
KW - kernel adaptive filtering
KW - survival information potential
UR - https://www.scopus.com/pages/publications/84893590589
U2 - 10.1109/IJCNN.2013.6706866
DO - 10.1109/IJCNN.2013.6706866
M3 - 会议稿件
AN - SCOPUS:84893590589
SN - 9781467361293
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2013 International Joint Conference on Neural Networks, IJCNN 2013
T2 - 2013 International Joint Conference on Neural Networks, IJCNN 2013
Y2 - 4 August 2013 through 9 August 2013
ER -