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IET Signal Processing
Article . 2018 . Peer-reviewed
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Realising the decomposition of a multi‐frequency signal under the coloured noise background by the adaptive stochastic resonance in the non‐linear system with periodic potential

Authors: Huang, Xiaogang; Zhang, Jingling; Lv, Meilei; Shen, Gang; Yang, Jianhua;

Realising the decomposition of a multi‐frequency signal under the coloured noise background by the adaptive stochastic resonance in the non‐linear system with periodic potential

Abstract

The authors investigate a multi‐frequency signal which is decomposed failure by the traditional empirical mode decomposition (EMD) method. Moreover, the multi‐frequency signal submerged in the coloured noise increases the difficulty in signal decomposition. As a result, this noisy signal is decomposed unsuccessfully by the cooperation of the adaptive stochastic resonance (SR) in the classic bistable system and EMD. Then, a method combined adaptive SR in the periodic potential system and EMD is put forward to realise the decomposition. Meanwhile, the random particle swarm optimisation algorithm is applied to reach the optimal situation when signal‐to‐noise ratio attains the maximum value. Different simulation results verify the effectiveness of the proposed method. The proposed method might be useful in dealing with signal processing problems.

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Keywords

signal‐to‐noise ratio, B0260 Optimisation techniques, multifrequency signal decomposition, signal processing problems, nonlinear system, C1260S Signal processing theory, Engineering, EMD method, random particle swarm optimisation algorithm, particle swarm optimisation, adaptive signal processing, periodic potential system, adaptive stochastic resonance, C1180 Optimisation techniques, B6140 Signal processing and detection, random processes, classic bistable system, B0240Z Other topics in statistics, C1140Z Other topics in statistics, coloured noise background, stochastic processes, empirical mode decomposition method, nonlinear systems, Electrical Engineering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
gold