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2nd West Asian Colloquium on Optical Wireless Communications (WACOWC)

作者： Mostafapour, Ehsan Dizajdizi, Reza Zare Gui, Guan Rezaei, Hassan Naghiloo, Jaleh Aminfar, Amir Heydarlou, Homayoon Nouri Urmia Univ Dept Elect Engn Orumiyeh Iran Urmia Azad Univ Dept Elect Engn Orumiyeh Iran Nanjing Univ Posts & Telecommun Coll Telecommun & Informat Engn Nanjing Jiangsu Peoples R China Sharif Univ Technol Shahid Rezaei Res Ctr Tehran Iran

ISBN: (纸本)9781728137674

This paper considers the possibility and the details of implementing adaptive networks with visible light communication technology. Adaptive networks have various indoor and outdoor applications hence, their implementations with light waves face with different problems. Almost all free space optical (FSO) communication systems must deal with two channel deficiencies namely, optical noise and channel turbulence. Both channel noise and turbulence follow certain distributions that we explain in detail. In this paper, we analyze the effects of these disturbances on the estimation performance of incremental adaptive networks and present the results using various simulations. The results are presented by the means of mean square error values. Also, for Gaussian noise and Gamma-Gamma turbulence models we derived the theoretical mean square deviation (MSD) and excess mean square error (EMSE) values and compared them with the simulation outcomes.

关键词： Adaptive networks Incremental adaptation optical links least mean square algorithm Gamma-Gamma distribution

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Application of least mean square algorithm to suppression of maglev track-induced self-excited vibration

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JOURNAL OF SOUND AND VIBRATION 2011年第24期330卷 5791-5811页

作者： Zhou, D. F. Li, J. Hansen, C. H. Natl Univ Def Technol Maglev Engn Ctr Changsha 410073 Hunan Peoples R China Univ Adelaide Sch Mech Engn Adelaide SA 5005 Australia

Track-induced self-excited vibration is commonly encountered in EMS (electromagnetic suspension) maglev systems, and a solution to this problem is important in enabling the commercial widespread implementation of maglev systems. Here, the coupled model of the steel track and the magnetic levitation system is developed, and its stability is investigated using the Nyquist criterion. The harmonic balance method is employed to investigate the stability and amplitude of the self-excited vibration, which provides an explanation of the phenomenon that track-induced self-excited vibration generally occurs at a specified amplitude and frequency. To eliminate the self-excited vibration, an improved LMS (least mean square) cancellation algorithm with phase correction (C-LMS) is employed. The harmonic balance analysis shows that the C-LMS cancellation algorithm can completely suppress the self-excited vibration. To achieve adaptive cancellation, a frequency estimator similar to the tuner of a TV receiver is employed to provide the C-LMS algorithm with a roughly estimated reference frequency. Numerical simulation and experiments undertaken on the CMS-04 vehicle show that the proposed adaptive C-LMS algorithm can effectively eliminate the self-excited vibration over a wide frequency range, and that the robustness of the algorithm suggests excellent potential for application to EMS maglev systems. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： maglev track Nyquist criterion Magnetic levitation Television receivers Magnetic levitation systems least mean square algorithm self induced vibration Tuner Device Component

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On distributed non-linear active noise control using diffusion collaborative learning strategy

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IET SIGNAL PROCESSING 2018年第4期12卷 410-421页

作者： Kukde, Ruchi Panda, Ganapati Manikandan, M. Sabarimalai Indian Inst Technol Bhubaneswar Bhubaneswar Odisha India

Active noise control in a non-linear spatial region is a challenging problem, especially for low-frequency noise control applications. The investigation of the existing literature reveals that this problem is tackled by systems with multiple sensors and loudspeakers with a centralised processor. However, the use of centralised techniques is bulky, computationally expensive and lacks scalability. Therefore, the authors propose a distributed learning approach for noise cancellation using a diffusion collaborative strategy. The proposed Legendre-functional link network diffusion filtered s least mean square (FsLMS) algorithm is compared with the standard multi-channel FsLMS algorithm. For different non-linear scenarios, the performance of the proposed method is evaluated in terms of noise reduction performance and computational complexity. It is demonstrated that the proposed method offers significant improvement in noise mitigation performance and computational load as compared with its centralised multi-channel counterpart.

关键词： active noise control loudspeakers least mean squares methods computational complexity distributed nonlinear active noise control diffusion collaborative learning strategy nonlinear spatial region low-frequency noise control multiple sensors loudspeakers centralised processor distributed learning approach noise cancellation Legendre-functional link network diffusion least mean square algorithm standard multichannel FsLMS algorithm noise reduction performance computational complexity centralised multichannel counterpart

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Design of thinned fractal antenna arrays for adaptive beam forming and sidelobe reduction

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IET MICROWAVES ANTENNAS & PROPAGATION 2018年第3期12卷 435-441页

作者： El-Khamy, Said E. Eltrass, Ahmed S. El-Sayed, Huda F. Alexandria Univ Dept Elect Engn Alexandria 21544 Egypt Pharos Univ Dept Basic Sci Alexandria Egypt

This study introduces, for the first time, a new design methodology that combines the unique multi-band features of thinned fractal antenna arrays with the adaptive beamforming requirements. The major challenges of fractal array design are the high sidelobe level (SLL), the huge number of elements at higher-growth stages, and the radiation pattern synthesis. In this study, the ant colony optimisation algorithm is utilised for thinning fractal arrays by estimating the optimum combination of on' and off' elements corresponding to lowest possible SLL, while the least mean square algorithm is investigated as an adaptive beamforming method in the proposed design. The capability of the proposed design is demonstrated by investigating hexagonal and pentagonal fractal antenna arrays under various parameter regimes. The results show that the proposed design is much superior in terms of multi-band frequency operation, array element reduction, and beamforming accuracy. This reveals the effectiveness of the proposed technique as a promising design in smart antenna technology.

关键词： fractal antennas array signal processing antenna radiation patterns ant colony optimisation least mean squares methods adaptive antenna arrays thinned fractal antenna arrays adaptive beam forming method sidelobe reduction multiband features fractal array design high sidelobe level radiation pattern synthesis ant colony optimisation algorithm least mean square algorithm pentagonal fractal antenna arrays hexagonal fractal antenna arrays multiband frequency operation array element reduction smart antenna technology

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A novel LMS algorithm for ECG signal preprocessing and KNN classifier based abnormality detection

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第8期77卷 10365-10374页

作者： Venkatesan, C. Karthigaikumar, P. Varatharajan, R. Anna Univ Fac Informat & Commun Engn Chennai Tamil Nadu India Karpagam Coll Engn Dept Elect & Commun Engn Coimbatore Tamil Nadu India Sri Ramanujar Engn Coll Dept Elect & Commun Engn Chennai Tamil Nadu India

ECG signal abnormality detection is useful for identifying heart related problems. Two popular abnormality detection techniques are ischaemic beat classification and arrhythmic beat classification. In this work, ECG signal preprocessing and KNN based arrhythmic beat classification are performed to categorize into normal and abnormal subjects. LMS based adaptive filters are used in ECG signal preprocessing, but they consume more time for processing due to long critical path. To overcome this problem, a novel adaptive filter with delayed error normalized LMS algorithm is utilized to attain high speed and low latency design. Low power design is achieved in this design by applying pipelining concept in the error feedback path. R-peak detection is carried out in the preprocessed signal using wavelets for HRV feature extraction. Arrhythmic beat classification is carried out by KNN classifier on HRV feature extracted signal. Classification performance reveals that the proposed DWT with KNN classifier provides the accuracy of 97.5% which is better than other machine leaning techniques.

关键词： ECG noise removal Adaptive filter least mean square algorithm Discrete wavelet transform Machine learning KNN classifier

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Blind adaptive channel mismatch equalisation method for GNSS antenna arrays

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IET RADAR SONAR AND NAVIGATION 2018年第4期12卷 383-389页

作者： Lu, Zukun Chen, Huaming Chen, Feiqiang Nie, Junwei Ou, Gang Natl Univ Def Technol Coll Elect Sci 109 Deya Rd Changsha Hunan Peoples R China

A blind adaptive channel mismatch equalisation method for global navigation satellite system (GNSS) antenna arrays is proposed. The anti-jamming performance of the antenna arrays is limited by the channel mismatch that is a relative characteristic of each radio frequency channel but not an absolute non-ideal characteristic. To pre-process the received data in the frequency domain, the least mean square (LMS) algorithm is used. The reference signal in LMS is the received data in the reference element. The purpose of pre-processing is to make the received data in the other elements approach the reference signal, which, in essence, is to equalise the mismatched channel. Without any auxiliary sensors and calibration source, this method can estimate the channel characteristics relative to the reference elements. Simulations and experimental results show that the proposed method is significant in improving the anti-jamming performance.

关键词： channel estimation blind equalisers adaptive equalisers satellite navigation satellite antennas antenna arrays jamming interference suppression least mean squares methods frequency-domain analysis blind adaptive channel mismatch equalisation method GNSS antenna array Global Navigation Satellite System antijamming performance radiofrequency channel least mean square algorithm LMS algorithm frequency domain algorithm auxiliary sensor calibration source channel estimation

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An improved anti-forensics JPEG compression using least Cuckoo Search algorithm

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IMAGING SCIENCE JOURNAL 2018年第3期66卷 169-183页

作者： Shelke, Priya M. Prasad, Rajesh S. Vishwakarma Inst Informat Technol Pune Maharashtra India STESs Sinhgad Inst Technol & Sci Pune Maharashtra India

The lossy nature of the JPEG compression leaves traces which are utilized by the forensic agents to identify the local tampering in the image. In this paper, a tricky anti-forensic method has been proposed to remove the traces left by the JPEG compression in both the spatial domain and discrete cosine transform domain. A novel least Cuckoo Search algorithm is devised in the proposed anti-forensic compression scheme. Moreover, a new fitness function called histogram deviation is formulated in the optimization algorithm. The experimentation of the proposed anti-forensic compression scheme is performed over uncompressed images from UCID database. The performance of the proposed method is evaluated, and it is compared with the existing methods using PSNR, MSE and classification accuracy as measures. The experimentation ensued with promising results, i.e. accuracy of 0.97, PSNR of 44.34dB, and MSE of 0.1789 which prove the efficacy of the proposed method.

关键词： JPEG anti-forensics JPEG compression least mean square algorithm Cuckoo Search optimization algorithm

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Extensive simulation of fibre non-linearity mitigation in a CO-OFDM-WDM long-haul communication system

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IET OPTOELECTRONICS 2018年第5期12卷 258-262页

作者： Mhatli, Sofien Mrabet, Hichem Amari, Abdelkerim Carthage Univ SERCOM Labs 2078 Tunisia Polytech Sch Tunis Tunisia Saudi Elect Univ Medina Branch Coll Computat & Informat IT Dept Medina Saudi Arabia Mem Univ Newfoundland Fac Engn & Appl Sci St John NF A1B 3X5 Canada

In this study, a performance comparison of fibre non-linearity mitigation is performed in the context of 10 and 20Gb/s coherent optical orthogonal frequency-division multiplexing and wavelength division multiplexing (CO-OFDM-WDM). The authors compare two regression methods based on the third-order Volterra series and least mean square algorithm in terms of the bit error rate (BER) for different transmission distances and modulation formats. They also evaluate the BER as a function of the number of OFDM subcarriers for the Volterra-based non-linear equaliser (VNLE). In addition, by increasing the order of the VNLE from third-order to fifth-order series, a significant increase of performance is obtained for 100Gb/s CO-OFDM-WDM system. Likewise, a comparison study of 16-QAM 40Gb/s CO-OFDM system is performed as a function of Q-factor for support vector machine, Volterra equaliser and linear equaliser, respectively.

关键词： wavelength division multiplexing optical fibre communication support vector machines telecommunication channels Volterra series optical modulation error statistics equalisers OFDM modulation quadrature amplitude modulation least mean squares methods Q-factor regression analysis VNLE fifth-order series CO-OFDM-WDM system linear equaliser CO-OFDM-WDM long-haul communication system performance comparison coherent optical orthogonal frequency-division multiplexing regression methods least mean square algorithm bit error rate BER OFDM subcarriers Volterra-based nonlinear equaliser fibre nonlinearity mitigation transmission distances 16-QAM CO-OFDM system Q-factor support vector machine wavelength division multiplexing third-order Volterra series modulation formats

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An Efficient Noise Removal Technique Using Modified Error Normalized LMS algorithm

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NATIONAL ACADEMY SCIENCE LETTERS-INDIA 2018年第3期41卷 155-159页

作者： Venkatesan, C. Karthigaikumar, P. Anna Univ Madras Tamil Nadu India Karpagam Coll Engn Coimbatore Tamil Nadu India

Adaptive filters are increasingly popular in electrocardiogram noise cancellation due to their inherent ability to deal with nonstationary signals. In the past, adaptive filters with least mean square (LMS) algorithm and normalized LMS algorithm have been used for updating coefficients which is simple and provides satisfactory convergence performance. However, the LMS based adaptive filters use a long critical path to obtain the output. The critical path is generally reduced by pipelined structures with delay elements so that the desired sample period can be attained. In this paper, a delayed error normalized LMS adaptive filter is proposed to achieve high speed and low latency design with less computational elements. Simulation results show that the proposed technique provides better convergence performance with least mean square error.

关键词： ECG noise removal Adaptive filter least mean square algorithm mean square error (MSE)

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Robust Variable Zero Attractor Controller Based ZA-LMS algorithm for Variable Sparsity Environment

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NATIONAL ACADEMY SCIENCE LETTERS-INDIA 2018年第2期41卷 85-89页

作者： Radhika, S. Arumugam, Sivabalan Sathyabama Univ Fac Elect & Elect Engn Madras Tamil Nadu India NEC Mobile Networks Excellence Ctr Madras Tamil Nadu India

The zero attraction least mean square algorithm (ZA-LMS) provides excellent performance than LMS algorithm when the system is sparse. But when the sparsity level decreases, the performance of ZA-LMS is worse than standard LMS. Hence a novel approach is proposed to work in variable sparsity environment, i.e. the fixed zero attractor controller is replaced by a variable one and the variation is done by comparing the instantaneous error with a threshold which is based on steady state mean square error (MSE) of standard LMS algorithm. Simulations were performed to compare the proposed variable ZA-LMS (VZA-LMS) algorithm with LMS and ZA-LMS algorithms. The proposed algorithm is tested for non sparse, semi sparse and sparse systems and it is found that it converges to a steady state value equal to LMS when the system is non sparse and in case of sparse and semi sparse systems, the steady state MSE is less than LMS and ZA-LMS, thus making the algorithm robust against variable sparsity conditions.

关键词： least mean square algorithm Sparsity Steady state mean square error Zero attraction Convergence

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