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6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM)

作者： Wang, Lingyin Liu, Ju Zhang, Guowei Shandong Univ Sch Informat Sci & Engn Jinan 250100 Peoples R China

ISBN: (纸本)9781424437092

As a promising scheme, partial transmit sequences (PTS) provides an effective solution for peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals. However, the main drawback of original PTS (O-PTS) is the large computational complexity. In this paper, a reduced computational complexity partial transmit sequences (RCC-PTS) is proposed. In RCC-PTS, a low complexity phase weighting process is implemented, where the relationship between phase weighting sequences is considered and the computation for candidate signals is simplified by making use of this inherent feature. Theoretical analysis and simulation results show that, compared with O-PTS, our RCC-PTS can not only reduce computational complexity clearly but also has an advantage of no loss in PAPR reduction performance.

关键词： OFDM modulation OFDM signals communication complexity orthogonal frequency division multiplexing signal partial transmit sequences peak-to-average power ratio reduction phase weighting process reduced computational complexity

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Efficient CIC-based architecture with improved aliasing rejection and reduced computational complexity

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ELECTRONICS LETTERS 2016年第15期52卷 1294-+页

作者： Romero, D. E. T. Inst IPN ESCOM Sch CONACYT Mexico City 07738 DF Mexico

A useful cascaded integrator comb (CIC)-based architecture is presented that improves the worst-case alias rejection of the CIC filter and simultaneously reduces the computational load of its integration section. Since regularity and simplicity are acceptably preserved, the proposed design outperforms other recent CIC-based architectures from literature where these two desirable characteristics are severely affected.

关键词： comb filters computational complexity CIC-based architecture cascaded integrator comb reduced computational complexity worst-case alias rejection

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A new two-dimensional parallel block adaptive filter with reduced computational complexity

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1998年第6期E81A卷 1008-1012页

作者： Kinjo, S Oshiro, M Ochi, H Texas Instruments Inc Tsukuba Res & Dev Ctr Ltd Tsukuba Ibaraki 3050841 Japan Univ Ryukyus Dept Informat Engn Okinawa 9030213 Japan

Two-dimensional (2-D) adaptive digital filters (ADFs) for 2-D signal processing have become a fascinating area of the adaptive signal processing. However, conventional 2-D FIR ADF's require a lot of computations. For example, the TDLMS requires 2N(2) multiplications per pixel. We propose a new 2-D adaptive filter using the FFTs. The proposed adaptive filter carries out the fast convolution using overlap-save method, and has parallel structure. Thus, we can reduce the computational complexity to O(log(2) N) per pixel.

关键词： two-dimensional adaptive filter DFT filter bank reduced computational complexity

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computationally-efficient nonlinear model predictive control of wave energy converters with imperfect wave excitation previews

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OCEAN ENGINEERING 2025年 319卷

作者： Zhan, Siyuan Chen, Yutao Ringwood, John, V Trinity Coll Dublin Dept Mech Mfg & Biomed Engn Dublin D02 PN40 Ireland Fuzhou Univ Sch Elect Engn & Automat Fuzhou 350025 Peoples R China Maynooth Univ Ctr Ocean Energy Res Maynooth W23F2H6 Kildare Ireland

Energy maximising (EM) control of wave energy converters (WECs) is a noncausal problem, where wave prediction information can be used to increase the energy conversion rate significantly. However, current approaches do not consider the prediction error evolution in the control formulation process, leading to potential unpredictable performance degradation. Moreover, most existing real-time WEC control approaches assume linear dynamics, motivated by their simplicity and mild computational cost and, thus, are not effective for real-time control for WECs with nonlinear dynamics. Targeting imperfect wave prediction and nonlinear WEC dynamics, this paper proposes a computationally-efficient nonlinear MPC (NMPC) scheme for WECs with (typically) imperfect wave excitation preview. This is achieved by introducing an input move blocking scheme when formulating and solving the online optimisation problem, i.e., defining finer discretisation grids for the control input and wave prediction at the early stages of the prediction horizon, where the wave prediction is more accurate, and coarser grids at the latter stages of the horizon, to reflect less inaccurate wave prediction information. Numerical simulation results are presented, based on a conceptual nonlinear point-absorber WEC, to verify the efficacy of the proposed NMPC method, in terms of produced energy, computational complexity, and robustness against wave prediction inaccuracy.

关键词： Nonlinear model predictive control Wave prediction Wave energy converter reduced computational complexity

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Improved least-squares identification for multiple-output non-linear stochastic systems

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IET CONTROL THEORY AND APPLICATIONS 2020年第7期14卷 964-971页

作者： Xia, Huafeng Ji, Yan Yang, Yongqing Ding, Feng Hayat, Tasawar Jiangnan Univ Key Lab Adv Proc Control Light Ind Sch Internet Things Engn Minist Educ Wuxi 214122 Jiangsu Peoples R China Taizhou Univ Taizhou Elect Power Convers & Control Engn Techno Taizhou 225300 Peoples R China Qingdao Univ Sci & Technol Coll Automat & Elect Engn Qingdao 266061 Peoples R China King Abdulaziz Univ Dept Math Jeddah 21589 Saudi Arabia

This study considers the identification problems of multiple-output non-linear equation-error moving average systems. There exist the product items of the parameters between the non-linear and linear parts. To solve this difficulty, the key term separation technique is adopted. By using the model decomposition technique and the hierarchical identification principle, a maximum likelihood-based recursive extended least-squares estimation algorithm with reduced computational complexity is presented to estimate the parameters of the non-linear part and the linear part interactively. The simulation results demonstrate the effectiveness of the proposed method.

关键词： maximum likelihood estimation least squares approximations stochastic systems recursive estimation computational complexity linear systems nonlinear systems nonlinear equations identification problems multiple-output nonlinear equation-error moving average systems linear parts key term separation technique model decomposition technique hierarchical identification principle nonlinear part multiple-output nonlinear stochastic systems recursive extended least-squares estimation algorithm maximum likelihood-based estimation algorithm parameter estimation reduced computational complexity improved least-squares identification

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New Algorithms for Evaluating the Log-Likelihood Function Derivatives in the AI-REML Method

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2009年第6期38卷 1348-1364页

作者： Mishchenko, Kateryna Neytcheva, Maya Malardalen Univ Sch Educ Culture & Commun SE-72123 Vasteras Sweden Uppsala Univ Dept Informat Technol Div Comp Sci Uppsala Sweden

In this study, we propose several improvements of the Average Information Restricted Maximum Likelihood algorithms for estimating the variance components for genetic mapping of quantitative traits. The improved methods are applicable when two variance components are to be estimated. The improvements are related to the algebraic part of the methods and utilize the properties of the underlying matrix structures. In contrast to previously developed algorithms, the explicit computation of a matrix inverse is replaced by the solution of a linear system of equations with multiple right-hand sides, based on a particular matrix decomposition. The computational costs of the proposed algorithms are analyzed and compared.

关键词： Identity-by-descent (IBD) matrix reduced computational complexity Restricted maximum likelihood algorithm (REML) Spectral decomposition Variance component estimation Woodbury's formula

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A Fast Model Predictive Control Framework for Multi-Float and Multi-Mode-Motion Wave Energy Converters

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2023年第3期31卷 1443-1450页

作者： Zhan, Siyuan Stansby, Peter Liao, Zhijing Li, Guang Maynooth Univ Ctr Ocean Energy Res Maynooth W23 F2H6 Ireland Univ Manchester Dept Mech Aerosp & Civil Engn Manchester M13 9PL England Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL England

Recently, multi-float and multi-mode-motion wave energy converters (M-WECs) have been developed to improve energy conversion capability. Although model predictive control (MPC) can be very effective to solve the constrained energy maximization control problem of point absorber WECs, the increased complexity of the M-WEC hydrodynamics can bring significant challenges due to computational demand. This brief proposes a novel computational-efficient fast MPC (FMPC) design method for the M-WECs requiring complex linear hydrodynamic models. The controller design objective is to maximize the energy conversion with some available wave forecasting information and to satisfy state and control input constraints to ensure safe operation. The main advantage of the proposed FMPC is the reduced computational burden with a negligible impact on performance. A demonstrative numerical simulation based on a 1:50 laboratory-scale M-WEC design, M4, for which linear hydrodynamics has been verified experimentally, is presented to verify the efficacy of the proposed control method in terms of both computational load and energy output.

关键词： Force Torque Fasteners Hydrodynamics computational modeling Predictive models Surges Model predictive control (MPC) reduced computational complexity wave energy

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Control Barrier Proximal Dynamics: A Contraction Theoretic Approach for Safety Verification

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IEEE CONTROL SYSTEMS LETTERS 2024年 8卷 880-885页

作者： Marvi, Zahra Bullo, Francesco Alleyne, Andrew G. Univ Minnesota Mech Engn Dept Minneapolis MN 55455 USA Univ Calif Santa Barbara Mech Engn Dept Santa Barbara CA 93106 USA Univ Calif Santa Barbara Ctr Control Dynam Syst & Computat Santa Barbara 93106 CA USA

In this letter, we present a computationally-efficient barrier function-based contraction-theoretic approach for safety verification. We adopt a dynamical system approach towards Control Barrier Function (CBF)-based Quadratic Programming (QP). To mitigate the computational complexity of online solutions to time-varying convex optimization, we integrate tools from contraction theory and proximal primal-dual gradient dynamics (PDGD) to provide an arbitrarily close approximation of the optimal solution. Subsequently, we adopt this result for the CBF-based QP, offering a computationally-efficient and scalable safe control design termed Control Barrier Proximal Dynamics (CBPD). The contractivity of the CBPD is then leveraged to characterize the safety of the system. We demonstrate that adopting CBPD under a technical assumption guarantees the safety specifications of the system with a bounded violation margin, which can be made arbitrarily small. Additionally, a computational analysis depicts substantial improvements in efficiency and scalability compared to the state-of-the-art. Finally, we evaluate the effectiveness of the proposed method through the simulation of a battery management problem with electro-thermal constraints.

关键词： Safety Dynamical systems Optimization Vectors Convex functions Control design computational efficiency Control barrier function contraction theory convex optimization proximal primal dual gradient dynamics reduced computational complexity safety

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High-Power Interference Suppression via reduced complexity Adaptive Blind Beamforming

High-Power Interference Suppression via Reduced Complexity A...

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Conference on Wireless Sensing, Localization, and Processing V

作者： Okamoto, Garret Chen, Chih-Wei Adapt Commun Res Inc San Diego CA 92130 USA

ISBN: (纸本)9780819481702

This paper evaluates the ACRi Blind Beamforming (ABB) smart antenna algorithm which addresses the significant problem caused by high-power transmitters located in close proximity to users. Current solutions are overwhelmed by the rapid increase in number and variety of strong interference sources. ABB requires less computational complexity than standard algorithms, making it feasible to be added to current and next-generation systems, and provides a highly adaptive and reliable interference-resistant communications environment. Simulations show that ABB automatically nulls jamming signals that are 20 dB to 40 dB stronger than the user signal, achieving close to the theoretically best performance despite being a blind solution (no information required about the jammer or user signal) and its low computational requirements. Systems with a limited number of antennas are evaluated because legacy and current generation systems have as little as two antennas.

关键词： Adaptive Blind Beamforming Smart Antenna reduced computational complexity

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DOA Estimation with a Combination of Iterative MUSIC and SBL in Low SNR Conditions

DOA Estimation with a Combination of Iterative MUSIC and SBL...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Zhou, Mengfan Tian, Hui Fan, Shaoshuai Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

ISBN: (纸本)9781728195070

This paper proposes a two-stage direction-of-arrival (DOA) estimation method combining Multiple Signal Classification (MUSIC) with Sparse Bayesian Learning (SBL) algorithm. In the first stage, we take advantage of the divergence of noise power spectrum and have designed an iterative MUSIC method. Performing MUSIC iteratively, we can obtain an angle set, including all estimates of DOA. Then, we transfer the angle set to the next stage to pick the correct values out. In the second stage, the angle set acquired from the iterative MUSIC is utilized to constitute the dictionary matrix used in SBL, which can decrease the computational complexity effectively. Simulations indicate that the proposed method can achieve high estimation accuracy even when the Signal-to-Noise Ratio(SNR) is below 0dB with a DOA gap of 3 degrees, outperforming the conventional MUSIC and SBL algorithm.

关键词： Direction-of-Arrival Estimation Iterative MUSIC Sparse Bayesian Learning reduced computational complexity

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