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.
| Original language | English |
|---|---|
| Pages (from-to) | 340-349 |
| Number of pages | 10 |
| Journal | Signal Processing |
| Volume | 128 |
| DOIs | |
| Publication status | Published - 1 Nov 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Energy conservation relation
- Kernel method
- Least sum of exponentials
- Variable scaling factor
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
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