Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61605
Title: A class of improved least sum of exponentials algorithms
Authors: Wang, S
Zheng, Y
Duan, S
Wang, L
Tse, CK 
Keywords: Energy conservation relation
Kernel method
Least sum of exponentials
Variable scaling factor
Issue Date: 2016
Publisher: Elsevier
Source: Signal processing, 2016, v. 128, p. 340-349 How to cite?
Journal: Signal processing 
Abstract: A class of improved least sum of exponentials (ILSE) algorithms is proposed by incorporating a scaling factor into the cost function of LSE in this paper. The even-order moment information regarding error is influenced by the scaling factor. However, the ILSE algorithm based on a fixed scaling factor can only provide a tradeoff between the convergence rate and steady-state excess-mean-square error (EMSE). Therefore, a variable scaling factor ILSE (VS-ILSE) algorithm is also proposed to improve the convergence rate and steady-state EMSE, simultaneously. To facilitate analysis, the energy conservation relation of ILSE is established, providing a sufficient condition for mean square convergence and a theoretical value of the steady-state EMSE. In addition, the kernel extensions of ILSE and VS-ILSE are further developed for performance improvement. Simulation results illustrate the theoretical analysis and the excellent performance of the proposed methods.
URI: http://hdl.handle.net/10397/61605
ISSN: 0165-1684
EISSN: 1872-7557
DOI: 10.1016/j.sigpro.2016.05.005
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