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Combining gradient-based and Thresholding Methods for Improved Signal Reconstruction Performance

JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2023年第5期95卷 643-656页

作者： Zaric, Maja Lakicevic Draganic, Andela Orovic, Irena Beko, Marko Stankovic, Srdan Univ Montenegro Fac Elect Engn Podgorica 81000 Montenegro Univ Lusofona COPELABS P-1700097 Lisbon Portugal Univ Lisbon Inst Telecomunicacoes Inst Super Tecn Lisbon Portugal

Analysis of sparse signals has been attracting the attention of the research community in recent years. Several approaches for sparse signal recovery have been developed to provide accurate recovery from a small portion of available data. This paper proposes an improved combined approach for both accurate and computationally efficient signal recovery. Particularly, the proposed approach uses the benefits of the gradient-based steepest descent method (that belongs to the convex optimization group of algorithms) in combination with a specially designed thresholding method. This approach includes solutions for several commonly used sparse bases - the discrete Fourier, discrete cosine transform, and discrete Hermite transform, but can be adapted for other transformations as well. The presented theory is experimentally evaluated and supported by empirical data. Various analytic and real-world signals are used to assess the performance of the proposed algorithm. The analyses are performed for different percentages of available samples. The complexity of the presented algorithm can be seen through the analog hardware implementation presented in this paper. Additionally, the user-friendly graphical interface is developed with a belonging signal database to ease usage and testing. The interface allows users to choose various parameters and to examine the performance of the proposed tool in different scenarios and transformation bases.

关键词： Compressive sensing gradient-based algorithm Hardware architecture Software tool Sparse signal processing Threshold

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An Integrated Framework for ARX Model Identification and Its Application to Lithium-Ion Battery

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Chen, Mengting Xie, Xiangpeng He, Chaoyue Ding, Jie Xiao, Min Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210003 Peoples R China Nanjing Univ Posts & Telecommun Sch Automat & Artificial Intelligence Nanjing 210023 Peoples R China

This article addresses the critical problem of real-time parameter estimation in dynamic systems using the autoregressive with exogenous input (ARX) model framework, with a particular focus on applications in lithium-ion batteries. The accurate and efficient parameter estimation is essential for optimizing system performance in various contexts. However, traditional gradient-based methods often encounter limitations, such as poor adaptability and reduced reliability under dynamic conditions. To address these challenges, this study proposes a hybrid gradient-based approach that integrates fractional-order gradients and a convex combination mechanism. This approach enables a more broader exploration of the optimization objective. A kernel function is introduced to dynamically adjust the weights of multi-innovation variables, reducing the impact of random errors in parameter estimation. Furthermore, the proposed ARX-based identification framework is tailored to the second-order RC equivalent circuit model (ECM) for lithium-ion batteries. Experimental results suggest that the proposed identification framework possesses the potential to achieve a more satisfactory performance than traditional methods.

关键词： Integrated circuit modeling Computational modeling Lithium-ion batteries Parameter estimation Accuracy Resistance Adaptation models Technological innovation Real-time systems Heuristic algorithms Fractional-order derivative gradient-based algorithm real-time identification system identification

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Subpixel Matching Using Double-Precision gradient-based Method for Digital Image Correlation

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SENSORS 2021年第9期21卷 3140-3140页

作者： Liu, Gang Li, Mengzhu Zhang, Weiqing Gu, Jiawei Chongqing Univ Sch Civil Engn 83 Shabei St Chongqing 400045 Peoples R China

Digital image correlation (DIC) for displacement and strain measurement has flourished in recent years. There are integer pixel and subpixel matching steps to extract displacement from a series of images in the DIC approach, and identification accuracy mainly depends on the latter step. A subpixel displacement matching method, named the double-precision gradient-based algorithm (DPG), is proposed in this study. After, the integer pixel displacement is identified using the coarse-fine search algorithm. In order to improve the accuracy and anti-noise capability in the subpixel extraction step, the traditional gradient-based method is used to analyze the data on the speckle patterns using the computer, and the influence of noise is considered. These two nearest integer pixels in one direction are both utilized as an interpolation center. Then, two subpixel displacements are extracted by the five-point bicubic spline interpolation algorithm using these two interpolation centers. A novel combination coefficient considering contaminated noises is presented to merge these two subpixel displacements to obtain the final identification displacement. Results from a simulated speckle pattern and a painted beam bending test show that the accuracy of the proposed method can be improved by four times that of the traditional gradient-based method that reaches the same high accuracy as the Newton-Raphson method. The accuracy of the proposed method efficiently reaches at 92.67%, higher than the Newton-Raphon method, and it has better anti-noise performance and stability.

关键词： displacement measurement digital image correlation subpixel matching gradient-based algorithm linear combination

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Consensus Control of a Class of Uncertain Nonlinear Multiagent Systems via gradient-based algorithms

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IEEE TRANSACTIONS ON CYBERNETICS 2019年第6期49卷 2085-2094页

作者： Li, Ranran Yang, Guang-Hong Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

This paper is concerned with the distributed optimization problem for a class of minimum-phase nonlinear multiagent systems with second relative degree. The target is to minimize a cost function composed of a group of convex local functions of the outputs in a cooperative manner. Novel state feedback control laws are first proposed and the consensus subject to the optimization constraint is achieved when the communication graph is directed. By replacing the derivatives of the outputs in the state feedback control laws with their estimations, the output feedback control laws are constructed and proved to achieve exponential consensus under the undirected graph. The effectiveness of the proposed control laws is validated by some simulations.

关键词： Consensus distributed optimization gradient-based algorithm nonlinear multiagent system

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An adaptive moment estimation framework for well placement optimization

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COMPUTATIONAL GEOSCIENCES 2022年第4期26卷 957-973页

作者： Arouri, Yazan Sayyafzadeh, Mohammad Univ Adelaide Australian Sch Petr & Energy Resources Adelaide SA 5005 Australia

In this study, we propose the use of a first-order gradient framework, the adaptive moment estimation (Adam), in conjunction with a stochastic gradient approximation, to well location and trajectory optimization problems. The Adam framework allows the incorporation of additional information from previous gradients to calculate variable-specific progression steps. As a result, this assists the search progression to be adjusted further for each variable and allows a convergence speed-up in problems where the gradients need to be approximated. We argue that under computational budget constraints, local optimization algorithms provide suitable solutions from a heuristic initial guess. Nonlinear constraints are taken into account to ensure the proposed solutions are not in violation of practical field considerations. The performance of the proposed algorithm is compared against steepest descent and generalized pattern search, using two case studies - the placement of four vertical wells and placement of 20 nonconventional (deviated, horizontal and/or slanted) wells. The results indicate that the proposed algorithm consistently outperforms the tested methods in terms computational efficiency and final optimum value. Additional discussions regarding nonconventional parameterization provide insights into simultaneous perturbation gradient approximations.

关键词： Well placement gradient-based algorithm Adaptive moment estimation Field development optimization

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A Simple Closed-Loop Method for Compensating the Impact of Antenna Misalignment in UCA-based OAM-MIMO Systems

A Simple Closed-Loop Method for Compensating the Impact of A...

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IEEE International Conference on Communications (IEEE ICC)

作者： Kamiya, Norifumi Sasaki, Eisaku NEC Corp Ltd Adv Network Res Labs Kawasaki Kanagawa Japan NEC Corp Ltd Wireless Transport Dev Dept Kawasaki Kanagawa Japan

ISBN: (纸本)9798350333077

In this paper, we consider a radio orbital angular momentum (OAM) communication system with uniform circular antenna arrays (UCAs) at both the transmitter and the receiver, which can be seen as a line-of-sight (LOS) multi-input multi-output (MIMO) system with discrete Fourier transform matrix as the precoding matrix. While the UCA-based OAM multiplexing can enhance the transmission capacity of LOS links, it is quite sensitive to antenna misalignment and multipath fading, which cause degradation of the capacity performance. In order to alleviate the capacity degradation, we propose a novel closed-loop OAM-MIMO system with adaptive phase-shift control and present a gradient-descent-based algorithm for optimizing the amount of the phase-shift. The gradients are computed at the receiver side and then fed back to the transmitter side. The amount of the feedback information is much less than that of the channel state information represented by the channel matrix. Simulation results show that the proposed algorithm performs very well even when the misalignment varies rapidly over time.

关键词： Orbital Angular Momentum (OAM) Multiplexing Line-of-Sight (LOS) MIMO Adaptive Phase-Shift Control gradient-based algorithm

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Investigating the Adoption of Hybrid Encrypted Cloud Data Deduplication With Game Theory

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2021年第3期32卷 587-600页

作者： Liang, Xueqin Yan, Zheng Deng, Robert H. Zheng, Qinghua Xidian Univ Sch Cyber Engn State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Aalto Univ Dept Commun & Networking Konemiehentie 2 Espoo 02150 Finland Singapore Management Univ Sch Informat Syst Singapore 188065 Singapore Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian 710049 Peoples R China

Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this article, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs). Then, we construct a multi-stage Stackelberg game, which consists of Holder Participation Game, Owner Online Game, and CSP Pricing Game, to capture the interactions among all system stakeholders. We further analyze the conditions of the existence of a sub-game perfect Nash Equilibrium and propose a gradient-based algorithm to help the stakeholders choose near-optimal strategies. Extensive experiments show the feasibility of the proposed algorithm in achieving the Nash Equilibrium of the Stackelberg game. Additionally, we investigate the effects of parameters related to CSP, data owners and data holders on H-DEDU adoption. Our study advises all stakeholders the best strategies to adopt H-DEDU.

关键词： Games Stakeholders Economics Biological system modeling Cloud computing Cryptography Game theory Cloud computing deduplication gradient-based algorithm multi-stage stackelberg game

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Simultaneous Efficiency and Starting Torque Optimization of a Line-Start Permanent-Magnet Synchronous Motor Using Two Different Optimization Approaches

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021年第10期46卷 9953-9964页

作者： Palangar, Mousalreza Faramarzi Mahmoudi, Amin Kahourzade, Solmaz Soong, Wen L. Flinders Univ S Australia Coll Sci & Engn Adelaide SA Australia Univ South Australia STEM Adelaide SA Australia Univ Adelaide Sch Elect & Elect Engn Adelaide SA 5005 Australia

Line-start permanent-magnet synchronous motors (LSPMSMs) have poorer starting performance than induction motors. Optimization focusing only on transient performance improvement of the LSPMSM may degrade steady-state performance, and vice versa. In fact, an optimization focusing on maximizing starting torque may reduce efficiency by up to approximately 7% and optimizing efficiency may cause degradation in starting torque by 5%. Hence, simultaneous steady-state and transient performance optimization of a 4-kW LSPMSM under a multi-objective function is examined in this study. Efficiency maximization and starting torque maximization are nominated as objective functions. Two different optimization approaches, a gradient-based algorithm and gradient-free algorithm, are employed to optimize the LSPMSM. Sequential nonlinear programming is used as the gradient-based algorithm in this study, and the gradient-free algorithm used is the genetic algorithm (GA). A comparative study of the algorithms' performance is presented. To provide an inclusive comparison of both algorithms' performance, a similar optimization study is implemented for a baseline induction motor. The results demonstrate that the multi-objective optimization improves steady-state and start-up performance of both motors. Results indicate that both algorithms converge reliably to almost the same optimum (objective) value. Depending on the nature of the optimization problem, number of design variables, and degree of convergence, the genetic algorithm requires many more evaluations than the gradient-based algorithm. Accordingly, optimization time required by the GA is more than the gradient-based algorithm under similar conditions.

关键词： Finite-element analysis gradient-based algorithm Genetic algorithm Line-start permanent magnet synchronous motor (LSPMSM) Induction motor (IM) Transient Steady state Optimization

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Optimal cross-layer resource allocation in fog computing: A market-based framework

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2023年 209卷

作者： Li, Shiyong Liu, Huan Li, Wenzhe Sun, Wei Yanshan Univ Sch Econ & Management Hebei St 438 Qinhuangdao 066000 Hebei Peoples R China

The potential upsides of fog computing are undeniable, including better near-real-time response, reduced transmission costs and analysis for IoT, which will further have a significant impact on operation of factories, enterprises, organizations and even the quality of our life. However, due to the resource-constrained nature, heterogeneity and distributed nodes, how to manage the extraordinarily complex fog computing resources is necessary to improve the QoE of users. This paper investigates the rational resource allocation for fog computing from the cross-layer point of perspective, and formulates the resource allocation scenario as Cloud- Fog-User market which is composed of cloud center devices, fog nodes, and user devices. Firstly, the resource market is divided into Cloud-Fog market containing cloud layer and fog layer, and Fog-User market containing fog layer and user layer based on different scenarios separately. The paper proposes a market-based framework for fog computing networks, which enables the cloud layer and the fog layer to allocate their resources in the form of pricing, payment and supply-demand relationship, while analyzes the relationship among resource allocation participants in the market. Then the paper investigates the utility optimization models from the viewpoints of both the participants of respective markets, so as to optimize optimal payment and optimal resource allocation via convex optimization techniques, and proposes a gradient-based iterative algorithm to optimize the utilities, respectively. Finally, experimental results have displayed the performance of convex analysis results and effectiveness of the proposed algorithm.

关键词： Fog computing Cross-layer design Market framework gradient-based algorithm Resource allocation Utility maximization

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A sequential finite element model updating routine to identify creep parameters for filament wound composite cylinders in aggressive environments

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COMPUTERS & STRUCTURES 2023年 276卷

作者： Almeida, Jose Humberto S. Lisboa, Tales, V Spickenheuer, Axel St-Pierre, Luc Queens Univ Belfast Sch Mech & Aerosp Engn Adv Composites Res Grp Belfast Antrim North Ireland Aalto Univ Dept Mech Engn Espoo Finland Leibniz Inst Polymerforsch Dresden eV Hohe Str 6 Dresden Germany

In this paper, a Finite Element Model Updating (FEMU) procedure is developed to find the best creep parameters for filament-wound cylinders under radial compression in harsh environmental conditions. Three winding angles are considered, each under three different hygrothermal conditions. The two-stage creep model captures i) primary creep through a time-hardening approach whilst ii) secondary creep is captured by Norton's law. Given the high number of parameters in this two-stage creep model and the complexity of determining them experimentally, the FEMU routine utilises an optimisation scheme that sequentially couples a Genetic algorithm (GA) with a gradient-based (GB) Levenberq-Marquardt algorithm (LMA) to find all required creep input parameters to feed the model that best simulates exper-imental results. This framework finds the global optimum through an initial screening of the optimum area within the design space with GA, clearing the path to allow the GB algorithm to find the global opti-mum, substantially reducing the chance or even avoiding falling in local minima. The global search is dri-ven by experimental data of cylinders loaded in radial compression under aggressive environments. The numerical results show excellent agreement with experimental results with reasonably low computa-tional efforts.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Creep modelling Finite element model updating Genetic algorithm gradient-based algorithm Filament winding

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