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Identification of Wiener time delay systems based on hierarchical gradient approach

IFAC-PapersOnLine 2015年第1期28卷 403-408页

作者： Atitallah, Asma Bedoui, Saïda Abderrahim, Kamel National Engineering Schoo Gabes University of Gabes Gabes6029 Tunisia

In this paper, we propose a hierarchical gradient based algorithm to identify simultaneously the parameters of the linear and nonlinear blocks and the time delay of Wiener time delay systems. We separate the nonlinear cost function into two cost functions and present the gradient algorithm for estimating directly the time delay and the parameters. Furthermore, we give an appropriate choice of convergence factor. Numerical simulation results are presented to demonstrate the performance of the proposed method. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Parameter estimation Cost functions Delay control systems Hierarchical systems Identification (control systems) Nonlinear systems Numerical methods Time delay Timing circuits Convergence factor gradient algorithm gradient approach gradient based algorithm Hierarchical approach Nonlinear cost functions Time delay systems Wiener systems

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Peak searching for multimodal optimization through gradient-based stochastic extremum seeking technique 8th

Peak searching for multimodal optimization through gradient-...

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8th International Conference on Applied Energy (ICAE)

作者： Yin, Chun Wu, Shanshan Zhou, Shiwei Wang, Wei Cheng, Yuhua Huang, Xuegang Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China China Aerodynam Res & Dev Ctr Mianyang 621000 Peoples R China

In this paper, a global peak searching algorithm is proposed for multimodal optimization problem. The proposed algorithm is built through combining gradient-based stochastic extremum seeking method with iterative approach. By increasing the initial search point, the gradient-based stochastic extremum seeking algorithm with different initial condition is iteratively operated to seek a list of the local extreme values near different initial points. Then, the global peak can be found by comparing the list of the local extreme values. The stability anlysis and working process of the global peak searching algorithm is proven. Simulation results are given to show the effectiveness of the proposed control method. (C) 2017 The Authors. Published by Elsevier Ltd.

关键词： Global searching gradient algorithm Initial point

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Inverse scattering in the multiple scattering regime using different gradient approximations

Inverse scattering in the multiple scattering regime using d...

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Mediterranean Microwave Symposium (MMS)

作者： Unger, Kevin D. Zhang, Ting Belkebir, Kamal Chaumet, Patrick C. Sentenac, Anne Aix Marseille Univ CNRS UMR 7249 Inst FresnelCent Marseille Marseille France

ISBN: (纸本)9781538655757

In this work we describe a linearized inverse method, based on the minimization of a cost functional, for reconstructing the permittivity of a target from scattered far-field in the multiple scattering regime. We show that accounting for multiple scattering in the calculation of the gradients of the cost functional ameliorates significantly the outcome of the reconstruction.

关键词： inverse problem multiple scattering gradient algorithm Born approximation

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Compressive Sensing Reconstruction of Video Data based on DCT and gradient-Descent Method 23

Compressive Sensing Reconstruction of Video Data based on DC...

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20th Telecommunications Forum (TELFOR)

作者： Stankovic, Isidora Draganic, Andjela Univ Montenegro Fac Elect Engn Dzordza Vasingtona Bb Podgorica 81000 Montenegro

ISBN: (纸本)9781509000555

The reconstruction of video with missing data using a gradient-based compressive sensing algorithm is presented in this paper. The video is assumed to have missing data randomly spread over the frames. Also, it has been assumed that the video frames are sparse in the DCT domain. The value of the gradient is calculated in the sparsity domain and then used to update the pixel values. The efficiency of the video reconstruction using the gradient-descent algorithm is analyzed in terms of the number of available samples and sparsity level, showing better reconstruction performance comparing to the greedy algorithm. Also, it has been shown that the gradient-based algorithm provides high quality reconstruction for real video sequences.

关键词： compressive sensing sparse signals video reconstruction gradient algorithm greedy algorithm

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Audio watermarking under gradient-based reconstruction attack 5

Audio watermarking under gradient-based reconstruction attac...

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5th Mediterranean Conference on Embedded Computing (MECO)

作者： Bratic, Dejan Vesovic, Filip Mijanovic, Vladimir Univ Montenegro Podgorica Montenegro

ISBN: (纸本)9781509022212

In order to protect digital data from the piracy, or, to allow ownership identification of the digital data, various techniques have been developed. In this paper, our focus will be on the protection, i.e. digital watermarking in the audio signals. The suitable time-frequency domain region is chosen for the watermark embedding. The robustness of the proposed procedure is tested under Compressive Sensing attack. Compressive Sensed signal, i.e., under-sampled signal, is recovered by using gradient based algorithm. The efficiency of the watermark detection is tested before and after the signal is attacked. The theory is proven with the experimental results, showing robustness of the proposed procedure even if the small number of signal samples is chosen as available for the signal reconstruction.

关键词： audio watermarking compressive sensing gradient algorithm time-frequency analysis

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Design and Testing of a Generalized Reduced gradient Code for Nonlinear Programming

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ACM Transactions on Mathematical Software (TOMS) 1978年第1期4卷 34-50页

作者： Lasdon, L.S. Waren, A.D. Jain, A. Ratner, M. Department of General Business School of Business Administration University of Texas Austin TX 78712 United States Department of Computer and Information Science Cleveland State University Cleveland OH 44115 United States Energy Systems Group Stanford Research Institute Menlo Park CA 94025 United States Department of Systems and Computer Science Case Western Reserve University Cleveland OH 44106 United States

An algorithm for solving nonlinear optimization problems is described along with its implementation as a Fortran program. Computational results are provided which compare its performance with that of other algorithms. The generalized reduced gradient (GRG) algorithm used is a nonlinear extension of the simplex method for linear programming. It is shown thatthe implementation is both robust and efficient. © 1978, ACM. All rights reserved.

关键词： constrained optimization gradient algorithm GRG mathematical programming nonlinear programming optimization reduced gradient software engineering

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Combination of gradient Based and Single Iteration Reconstruction algorithms for Sparse Signals 17

Combination of Gradient Based and Single Iteration Reconstru...

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IEEE EUROCON -17th International Conference on Smart Technologies

作者： Stankovic, Srdjan Vujovic, Stefan Orovic, Irena Dakovic, Milos Stankovic, Ljubisa Univ Montenegro Fac Elect Engn Podgorica 81000 Montenegro

ISBN: (纸本)9781509038435

A new algorithm implemented as combination of gradient based and single iteration reconstruction algorithms for compressively sensed sparse signals is proposed in the paper. A good feature of the gradient algorithm to perform reconstruction for a wide range of applications is combined with the speed of single iteration algorithm in order to perform faster reconstruction in the cases where single iteration algorithm cannot performs reconstruction. The proposed method is of special importance for any application where it is not possible to separate signal components from noise in sparse domain.

关键词： gradient algorithm compressive sensing sparse signals signal reconstruction

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Collaborative optimization design of process parameter and structural topology for laser additive manufacturing

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Chinese Journal of Aeronautics 2023年第1期36卷 456-467页

作者： Shaoying LI Hongkai WEI Shangqin YUAN Jihong ZHU Jiang LI Weihong ZHANG State IJR Center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical UniversityXi’an 710072China MIIT Lab of Metal Additive Manufacturing and Innovative Design Northwestern Polytechnical UniversityXi’an 710072China Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an 710072China

High-resolution laser additive manufacturing(LAM)significantly releases design free-dom,promoting the development of topology optimization(TO)and advancing structural design *** order to fully take advantage of voxelated forming methods and establish the quantitative relationship between the mechanical properties of printing components and multiple process factors(laser-and process-parameters),the concurrent optimization design method based on LAM should cover the process-performance *** study proposes a novel artificial intelligence-facilitated TO method for LAM to concurrently design microscale material property and macroscale structural topology of 3D components by adopting heuristic and gradient-based *** process–structure–property relationship of selective laser sintering is established by the back propagation neural network,and it is integrated into the TO algorithm for providing a systematic design scheme of structural topology and process *** with the classical optimization method,numerical examples show that this method is able to improve the mechanical performance of the macrostructure *** addition,the collaborative design method is able to be widely applied for complex functional part design and optimization,as well as case studies on artificial intelligence-facilitated product evaluation.

关键词： Back propagation neural network gradient algorithm Laser additive manufactur-ing Process–structure–property Topology optimization

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Identifying the heat source of biomedical heat transfer from final measurement data in the biological thermal-wave diffusion model

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Journal of Thermal Biology 2025年 129卷 104128页

作者： Xu-Wei Tie Zui-Cha Deng School of Mathematics and Physics Lanzhou Jiaotong University Lanzhou Gansu 730070 China Gansu Center for Fundamental Research in Complex Systems Analysis and Control Lanzhou Jiaotong University Lanzhou Gansu 730070 China

This study investigates the inverse problem of spatial heat source identification in biomedical heat transfer. Departing from conventional parabolic biomedical heat transfer models, our research focuses on more sophisticated and clinically relevant hyperbolic models, which offer enhanced suitability for biomedical engineering applications. Firstly, the uniqueness of the heat source was proved through the energy variational approach. Subsequently, the inverse problem is reformulated as an optimal control problem by employing total variation regularization within the framework of optimal control theory. Theoretical contributions include rigorous proofs of the existence of optimal solutions and their corresponding necessary conditions, complemented by the establishment of criteria for solution uniqueness and stability. Building upon these theoretical foundations, we have developed an innovative gradient algorithm, the efficacy of which has been validated through comprehensive numerical experiments utilizing clinically relevant electromagnetic radiation tissue heat transfer parameters commonly encountered in hyperthermia treatments.

关键词： Biomedical heat transfer gradient algorithm Heat source Inverse problem Numerical experiment Optimal solution

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Direct frequency estimation based adaptive algorithm for a second-order adaptive FIR notch filter

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SIGNAL PROCESSING 2008年第2期88卷 315-325页

作者： Punchalard, R. Lorsawatsiri, A. Loetwassana, W. Koseeyaporn, J. Wardkein, P. Roeksabutr, A. Mahanakorn Univ Technol Dept Telecommun Engn Bangkok 10530 Thailand King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Telecommun Engn Bangkok 10520 Thailand

This work deals with the problem of the frequency estimation of a sinusoidal signal corrupted by broad-band noise. The direct frequency estimation based adaptive algorithm for a second-order adaptive finite impulse response (FIR) notch filter (AFNF) is thus proposed. The proposed algorithm employs the bias removal technique to remove the bias existing in the estimated parameter. The performances including the rate of convergence and the mean square error (MSE) can be easily controlled by using only one parameter, i.e., step size parameter. Moreover, the proposed filter is simple to implement and suitable for real-time applications. In addition, the difference equations for the convergence in the mean and mean square, and the closed form expressions for the steady-state estimation bias and MSE are also carried out. Finally, the simulation results are provided to confirm the theoretical analysis. (c) 2007 Elsevier B.V. All rights reserved.

关键词： FIR notch filter gradient algorithm unbiased

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