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International Conference on Electronic Design

作者： Kumar, Sri J. Ravi Vaddadi, M. S. B. Saithej Penumala, Sunil Kumar Natl Inst Technol Dept Elect & Commun Engn Warangal 506004 Andhra Pradesh India

ISBN: (纸本)9781424423149

One of the classical signal processing problems is the distortion of transmitted signal by the channel before reaching the receiver. Channel Equalization is the solution for the so called problem. It has got a variety of solutions in the sense that the equalizer can be trained using different algorithms. In this paper besides the two standard adaptive algorithms LMS-Least Mean Square algorithm and rls-Recursive Least Square algorithm, biologically inspired evolutionary computing tools like Standard Genetic algorithm and Particle Swarm Optimization are adopted for channel equalization problem and the consequences are thoroughly studied under the headings convergence-rate, computational complexity, processing time etc..

关键词： Channel Equalization Genetic algorithm LMS algorithm Particle Swarm Optimization rls algorithm

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Analysis of different predistortion structures and efficient least square adaptive algorithms

Analysis of different predistortion structures and efficient...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Qian, YQ Li, Q Yao, TR Huazhong Univ Sci & Technol Dept Elect & Informat Wuhan 430074 Peoples R China

ISBN: (纸本)0780376633

Adaptive predistortion is one of the most promising techniques to overcome the nonlinear of High Power Amplifier (HPA). However, the adaptation of predistorter is not satisfied, for many efficient Least-Square (LS) adaptive algorithm cannot be used. In this paper, we analyze previously published predistortion structures and their difficulties in adapting with these efficient algorithms. The proposed structure constructs the desired output of the predistorter, so many efficient LS adaptive algorithms can be used directly, which implies that we can obtain faster convergence and lower complexity in adaptive process. Simulation results using Recursive Least Square (rls) algorithm in adaptation demonstrate about 30dB spectrum spreading improvement.

关键词： spread spectrum communication adaptive signal processing power amplifiers radiofrequency amplifiers least squares approximations distortion convergence of numerical methods predistortion structures efficient least-square adaptive algorithms adaptive predistortion nonlinear high power amplifier LS adaptive algorithms convergence complexity simulation results recursive least square algorithm rls algorithm spread spectrum spreading communication

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Joint estimation of IQ imbalance and PA nonlinearity: An iterative scheme

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DIGITAL SIGNAL PROCESSING 2024年 155卷

作者： Liu, Rui Xu, Xiaodong Qin, Xiaowei Univ Sci & Technol China Chinese Acad Sci Key Lab Wireless Opt Commun Hefei 230026 Anhui Peoples R China

Power amplifier (PA) nonlinearity and in-phase and quadrature-phase (IQ) imbalance in the transmitter are of critical concern in modern communication systems due to their significant impact on the transmitter performance. In this paper, in order to eliminate their effects without increasing the complexity at the transmitter, we propose an iterative structure for IQ imbalance and PA nonlinearity joint estimation at the receiver side. The strategic design aims to mitigate the influence of one distortion before estimating the other, ultimately improving the accuracy of estimating each distortion. The proposed approach comprises two primary modules: an IQ imbalance estimation module and a PA nonlinearity estimation module. In addition, there are two supporting modules, namely the PA nonlinearity compensation module and the IQ imbalance reconstruction module, positioned before these two primary modules respectively. Furthermore, we have derived the theoretical Cram & eacute;r-Rao lower bound (CRLB) for the joint distortion model of IQ imbalance and PA nonlinearity. Finally, extensive experiments are conducted to demonstrate the proposed algorithm's capability in estimating hardware distortions and mitigating them.

关键词： IQ imbalance PA nonlinearity Iterative estimation rls algorithm Polynomial inversion

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Active noise control in proximity of a tractor operator's head

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TRANSACTIONS OF THE ASAE 2001年第2期44卷 447-455页

作者： Peng, Y Sasao, A Shibusawa, S Kansas State Univ Dept Grain Sci & Ind Manhattan KS 66506 USA Tokyo Univ Agr & Technol Fuchu Tokyo Japan

To reduce the noise level near the head of agricultural machine operators, an active noise control (ANC) system, which uses sound wave interference, was developed. This system incorporates a recurrent least square (rls) algorithm into the feedback control loop. The ANC system was developed using a TMS320C25 high-speed digital signal processor (DSP). The noise-reduction effect of this system was examined at points near the ears of a tractor operator When the engine of a stopped tractor was running at rated speed, the overall sound pressure level (SPL) was reduced by about 5 to 6 dB, and the maximum SPL decreased approximately 18 dB. Since the computing speed and operational precision of the chosen DSP were limited, the noise-reduction effects of the system were not yet achievable for practical applications. As a result, the basis for future improvement and possible commercialization of the system using the TMS320C60 DSP which has higher operational performance, is presented.

关键词： active noise control agricultural machine noise rls algorithm feedback control

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Hybrid automaton-based disturbance-aware predictive control with receding horizon optimization for three-phase full-bridge inverters

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CONTROL ENGINEERING PRACTICE 2022年第0期121卷 104984-104984页

作者： Chen Zhengxi Shen Xun State Grid Corp China Global Energy Interconnect Grp Corp Ltd 8 Xuanwumennei St Beijing Peoples R China Tokyo Inst Technol Dept Syst & Control Engn Mekuro Ku Tokyo Japan

A data-driven disturbance-aware predictive control policy is proposed for DC-AC power inverters based on receding horizon optimization approach. First a discrete event-driven hybrid automaton model has been constructed for the nonlinear inverter system dynamics. A control problem of infinite discrete state-space transition sequence optimization is formulated. A receding-horizon-optimization-based hybrid controller is designed to solve the discrete optimization problem piece-wisely on-line. Accordingly, a disturbance-aware adaptive control is proposed, the external disturbance is sampled and estimated by an on-line Recursive Least Square (rls) algorithm. It is elaborated that the conventional PWM control solution is a subset of solutions of the proposed control strategy and the code-transition between them is provided. By adding extra PWM constraints to the proposed control strategy, an Optimal PWM Control Mode (OPCM) is introduced as example. The essence of OPCM is still a data-driven optimal solution based on MPC following pre-designated PWM constraints which is a modified sub-mode of ODCM and greatly reduces computational requirement. The proposed controller can freely operate under the original Optimal Discrete Control Mode (ODCM) and the OPCM. Numerical simulation results have verified that the proposed discrete control strategy has realized disturbance-aware adaptive control of DC-AC inversion against load-shift, and ODCM has better control performance than OPCM. In addition, the proposed modeling and control frame has potential to support other forms of control modes.

关键词： DC-AC inverter Discrete non-linear control Disturbance estimation Model predictive control Hybrid dynamic system Hybrid automaton model PWM Receding horizon optimization rls algorithm

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On-Line Evolution of Takagi-Sugeno Fuzzy Models

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IFAC Proceedings Volumes 2004年第16期37卷 67-72页

作者： Plamen Angelov José Victor António Dourado Dimitar Filev Department of Communications Systems Lancaster Universiy UK School of Technology and Management Polytechnic Institute of Leiria Portugal Adaptive Computation Group - CISUC University of Coimbra Portugal Ford Motor Co. USA

Evolving Takagi-Sugeno (eTS) fuzzy models and the method for their on-line identification has been recently introduced for both MISO and MIMO case. In this paper, the mechanism for rule-base evolution, one of the central points of the algorithm together with the recursive clustering and modified recursive least squares (rls) estimation, is studied in detail. Different scenarios are considered for the rule base upgrade and modification. The radius of influence of each fuzzy rule is considered to be a vector instead of a scalar as in the original eTS approach, allowing different areas of the data space to be covered by each input variable. Simulation results using a well-known benchmark (Mackey-Glass chaotic time-series prediction) are presented.

关键词： evolving Takagi-Sugeno fuzzy models rule-base evolution recursive clustering rls algorithm

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Adaptive Equalization algorithm for 60GHz Band in 5G

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电脑学刊 2017年第5期28卷 303-315页

作者： Ying Ou Xue-hua Li

An adaptive equalization algorithm suitable for CM7.1 channel is proposed to address the problem of channel multipath fading in 60 GHz pulse communication system. The steady-state and bit error rate performances of the proposed algorithm are analyzed based on the traditional LMS and rls algorithms, combined with the CM7.1 IEEE802.15.3c channel model, and compared with the traditional algorithm. Simulation results show that the algorithm reduces the computational complexity and verifies the feasibility of the algorithm in the 60 GHz pulse communication system with the premise of ensuring system reliability. Technical reference is provided for the application of high-capacity fifth-generation, high-frequency hot new empty scene.

关键词： 60 GHz pulse communication system adaptive equalization algorithms LMS algorithm rls algorithm

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Prediction Control algorithm for Close-loop Adaptive Optical System

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IFAC Proceedings Volumes 2013年第5期46卷 276-284页

作者： YAN Zhao-jun LI Xin-yang RAO Chang-hui The Laboratory of Adaptive Optics IOE Chinese Academy of Sciences Chengdu 610209 China The Key Laboratory of Adaptive Optics Chinese Academy of Sciences Chengdu 610209 China Graduate School of Chinese Academy of Sciences Beijing 100039 China

To reduce the effect of servo lag error in the close-loop adaptive optics system (AOS), a prediction control algorithm (PCA) is proposed in this paper. We describe a linear predictive controller that uses the historical voltages of deformable mirror to predict their future voltages in advance. The parameters of the predictor are optimized in real time by a modified Recursive Least-Square (rls) algorithm. Numerical simulations are carried out to show the significant improvements brought by the predictor. The close-loop Strehl Ratio of the residual wave-front error and the power spectrum density of the residual voltages of deformable mirror are calculated as the evaluation criterions. The comparison results between the PCA and the classical proportional integral (PI) control algorithm show that the residual errors caused by servo lag in the system could be more effectively reduced by using the PCA than using the classical PI control algorithm. In addition, the control bandwidth of AOS is improved by using the PCA.

关键词： Adaptive Optics prediction control algorithm rls algorithm PI control algorithm voltages of deformable mirror

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Two-dimensional adaptive filters based on the one-dimensional recursive least squares algorithm

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 1996年第7期79卷 92-101页

作者： Muneyasu, M Uemoto, E Hinamoto, T Faculty of Engineering Hiroshima University Higashi-Hiroshima Japan 739

This paper proposes a method for realizing two-dimensional (2-D) adaptive filters by applying a one-dimensional (1-D) recursive least squares (rls) algorithm. First, by applying a 1-D rls algorithm along horizontal and vertical directions, a novel 2-D adaptive algorithm is developed. ft is shown that the amount of calculations in the proposed algorithm is less than that in the misting 2-D rls algorithm. Moreover, the convergence properties of the proposed algorithm and its relation to the conventional 2-D rls algorithm are investigated. A method far accelerating the rate of convergence of the algorithm using a priori estimation error also is described. The proposed filter has good performance in nonstationary processes and the accuracy of convergence is better than that in the existing 2-D adaptive filters based on the least mean square (LMS) algorithm. Therefore, the proposed filter is suitable for processing an image with strongly nonstationary characteristics. Finally, the utility of the proposed filter is illustrated by applying it to 2-D system identification under a nonstationary environment as well as noise reduction of an image.

关键词： two-dimensional adaptive digital filter rls algorithm nonstationary inputs image processing

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Heart rate signal decomposition

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METHODS OF INFORMATION IN MEDICINE 2000年第2期39卷 200-203页

作者： Mizuta, H Yana, K Hosei Univ Dept Elect Informat Koganei Tokyo 1848584 Japan

This paper proposes a method for decomposing heart rate fluctuations into background, respiratory and blood pressure oriented fluctuations. A signal cancellation scheme using the adaptive rls algorithm has been introduced for canceling respiration and blood pressure oriented changes in the heart rate fluctuations. The computer simulation confirmed the validity of the proposed method. Then, heart rate fluctuations, instantaneous lung volume and blood pressure changes are simultaneously recorded from eight normal subjects aged 20-24 years. It was shown that after signal decomposition, the power spectrum of the heart rate showed a consistent monotonic 1/f(a) type pattern. The proposed method enables a clear interpretation of heart rate spectrum removing uncertain large individual variations due to the respiration and blood pressure change.

关键词： heart rate fluctuations 1/f fluctuations instantaneous lung volume blood pressure spectral analysis adaptive signal processing rls algorithm

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