Convergence analysis of Bessel beamformer and its comparison with LMS in adaptive array system
Purpose – The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important perf...
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| Published in | Compel Vol. 34; no. 3; pp. 952 - 961 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Bradford
Emerald Group Publishing Limited
01.01.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0332-1649 2054-5606 |
| DOI | 10.1108/COMPEL-07-2014-0184 |
Cover
| Abstract | Purpose
– The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important performance parameters, namely; convergence and mean square error. The proposed BLMS algorithm is implemented on digital signal processor along with antenna array to make it smart in wireless sensor networks.
Design/methodology/approach
– Convergence analysis is theoretically developed and verified through MatLab Software.
Findings
– Theoretical model is verified through simulation and its results are shown in the provided table.
Originality/value
– The theoretical model can obtain validation from well-known result of Wiener filter theory through principle of orthogonality. |
|---|---|
| AbstractList | Purpose
– The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important performance parameters, namely; convergence and mean square error. The proposed BLMS algorithm is implemented on digital signal processor along with antenna array to make it smart in wireless sensor networks.
Design/methodology/approach
– Convergence analysis is theoretically developed and verified through MatLab Software.
Findings
– Theoretical model is verified through simulation and its results are shown in the provided table.
Originality/value
– The theoretical model can obtain validation from well-known result of Wiener filter theory through principle of orthogonality. Purpose – The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important performance parameters, namely; convergence and mean square error. The proposed BLMS algorithm is implemented on digital signal processor along with antenna array to make it smart in wireless sensor networks. Design/methodology/approach – Convergence analysis is theoretically developed and verified through MatLab Software. Findings – Theoretical model is verified through simulation and its results are shown in the provided table. Originality/value – The theoretical model can obtain validation from well-known result of Wiener filter theory through principle of orthogonality. |
| Author | Akhtar, Pervez Yasin, M |
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| SubjectTerms | Adaptation Adaptive algorithms Adaptive systems Algorithms Antenna arrays Arrays Beamforming Communications systems Computer programs Computer simulation Convergence Design engineering Electrical & electronic engineering Electrical engineering Engineering Expected values Impact factors Least mean squares algorithm Mathematical models Matlab Mean square errors Microprocessors Orthogonality Product differentiation Remote sensors Sensor arrays Signal processing Simulation Wiener filtering Wireless sensor networks |
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| Title | Convergence analysis of Bessel beamformer and its comparison with LMS in adaptive array system |
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