Gradient Pursuit Identification Algorithm for MISO-FIR Systems

TAO Taiyang; LIU Yanjun; DING Feng

doi:10.13976/j.cnki.xk.2016.0151

Volume 45 Issue 2

Apr. 2016

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INFORMATION AND CONTROL > 2016 > 45(2): 151-156. > DOI: 10.13976/j.cnki.xk.2016.0151 CSTR: 32166.14.xk.2016.0151

TAO Taiyang, LIU Yanjun, DING Feng. Gradient Pursuit Identification Algorithm for MISO-FIR Systems[J]. INFORMATION AND CONTROL, 2016, 45(2): 151-156. DOI: 10.13976/j.cnki.xk.2016.0151

Citation:

TAO Taiyang, LIU Yanjun, DING Feng. Gradient Pursuit Identification Algorithm for MISO-FIR Systems[J]. INFORMATION AND CONTROL, 2016, 45(2): 151-156. DOI: 10.13976/j.cnki.xk.2016.0151

Citation:

TAO Taiyang, LIU Yanjun, DING Feng. Gradient Pursuit Identification Algorithm for MISO-FIR Systems[J]. INFORMATION AND CONTROL, 2016, 45(2): 151-156. DOI: 10.13976/j.cnki.xk.2016.0151

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Gradient Pursuit Identification Algorithm for MISO-FIR Systems

1.
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
2.
Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China

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Received Date: May 24, 2015
Revised Date: March 01, 2016
Available Online: December 07, 2022
Published Date: April 19, 2016

Graphical Abstract

Abstract

Abstract

For multiple-input single-output finite impulse response (MISO-FIR) systems with unknown time delays, we combine the matching pursuit method and the gradient search principle, according to the sparsity of the parameterized model based on the compressed sensing theory, and propose a gradient pursuit algorithm for simultaneously estimating parameters and time delays with limited sampling data. The proposed method reduces the associated computational burden compared with that of the orthogonal matching pursuit algorithm. The simulation results show the effectiveness of the proposed algorithm.
- gradient pursuit,
- parameter identification,
- time-delay estimation,
- orthogonal matching pursuit algorithm

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References

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