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gradient-based algorithm for designing sensing matrix considering real mutual coherence for compressed sensing systems

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IET SIGNAL PROCESSING 2017年第4期11卷 356-363页

作者： Jiang, Qianru Li, Sheng Bai, Huang de Lamare, Rodrigo C. He, Xiongxiong Zhejiang Univ Technol Coll Informat Engn Hangzhou Zhejiang Peoples R China Pontificia Univ Catolica Rio de Janeiro CETUC Rio de Janeiro Brazil Univ York Dept Elect York N Yorkshire England

This study deals with the issue of designing the sensing matrix for a compressed sensing (CS) system assuming that the dictionary is given. Traditionally, the measurement of small mutual coherence is considered to design the optimal sensing matrix so that the Gram of the equivalent dictionary is as close to the target Gram as possible, where the equivalent dictionary is not normalised. In other words, these algorithms are designed to solve the CS problem using an optimisation stage followed by normalisation. To achieve a global solution, a novel strategy of the sensing matrix design is proposed by using a gradient-based method, in which the measure of real mutual coherence for the equivalent dictionary is considered. According to this approach, a minimised objective function based on alternating minimisation is also developed through searching the target Gram within a set of relaxed equiangular tight frames. Some experiments are done to compare the performance of the newly designed sensing matrix with the existing ones under the condition that the dictionary is fixed. For the simulations of synthetic data and real image, the proposed approach provides better signal reconstruction accuracy.

关键词： compressed sensing image reconstruction matrix algebra minimisation gradient methods gradient-based algorithm real mutual coherence compressed sensing systems CS system optimal sensing matrix optimisation stage normalisation minimised objective function alternating minimisation image reconstruction

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Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields

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APPLIED MATHEMATICS AND COMPUTATION 2007年第2期185卷 823-833页

作者： Wang, Yi Hu, Jiankun Han, Fengling Royal Melbourne Inst Technol Sch Comp Sci & Informat Technol Melbourne Vic 3001 Australia

An accurate estimation of fingerprint orientation fields is an essential step in the overall fingerprint recognition process. Conventional gradient-based approaches are popular but very sensitive to noise. In this paper, we propose a novel implementation to improve the performance of gradient-based methods. The enhanced algorithm chooses the best orientation estimate from four overlapping neighborhoods of every image block, where the voting scheme is based on the reliability measures. We test our algorithm on real fingerprint images. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with modest computation time in comparison with other gradient-based methods. (c) 2006 Elsevier Inc. All rights reserved.

关键词： automatic fingerprint recognition orientation estimation gradient-based algorithm biometric authentication

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Novel Approach for InSAR Sensors Imaging via gradient-based algorithm for the Sparse Signal Reconstruction

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IEEE SENSORS JOURNAL 2018年第6期18卷 2385-2394页

作者： Wang, Yong Qian, Guangzhao Harbin Inst Technol Res Inst Elect Engn Technol Harbin 150001 Heilongjiang Peoples R China

It is well known that the interferometric synthetic aperture radar (InSAR) can be used to realize the reconstruction of digital elevation models. In common InSAR imaging, the signal is considered complete and accurate enough to generate high-quality images. However, only the sparse aperture measurements are available in the actual imaging process, which bring great challenges to the traditional InSAR imaging algorithms. In this paper, a new method for the 3-D InSAR imaging with sparse aperture is proposed. A gradient-based algorithm is adopted to obtain the high-precision reconstructed signal received from each sparse aperture antenna. Then, the 3-D geometric reconstruction of the target can be realized through the interferometric processing on the master and slave images. Finally, the experimental results are given to substantiate the effectiveness of the proposed algorithm.

关键词： 3-D InSAR imaging gradient-based algorithm Etna data image coregistration phase unwrapping Fourier transform (FT)

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A BLOCK gradient-based algorithm FOR ADAPTIVE IIR FILTERING

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SIGNAL PROCESSING 1995年第2期43卷 223-228页

作者： XI, JT CHICHARO, JF Department of Electrical and Computer Engineering University of Wollongong Northfield Avenue NSW 2522 Australia

This paper presents a new block gradient-based adaptive algorithm for Infinite Impulse Response (IIR) adaptive filters. In contrast with the Recursive Prediction Error (RPE) algorithm, the proposed algorithm employs more accurate gradient estimates. The gradients are calculated based on sampled data blocks, within which the filter coefficients are kept constant. The proposed approach is characterised by improved steady-state performance and reduced computational complexity when compared with the conventional RPE algorithm.

关键词： ADAPTIVE IIR FILTERING gradient-based algorithm

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Iris Recognition on Images Reconstructed with gradient-based algorithm 9

Iris Recognition on Images Reconstructed with Gradient-based...

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9th Mediterranean Conference on Embedded Computing (MECO)

作者： Radojicic, Tijana Bozovic, Milena Blagojevic, Nina Univ Montenegro Fac Elect Engn Dzordza Vasingtona Bb Podgorica 81000 Montenegro

ISBN: (纸本)9781728169491

Iris recognition is a procedure used for identifying persons based on unique patterns that are placed around pupil of the human eye. The aim is to localize the inner and outer boundaries of the iris in an image of the eye. Further, software detects and removes eyelids, eyelashes and specular reflections that often interfere with parts of the iris. In this paper we are discussing possibilities of different iris recognition software to perform recognition on images that are subject to compressive sensing approach. Namely, image is intentionally damaged according to the Compressive Sensing. Damaged (missing) image pixels are recovered by applying recovery algorithm. For the reconstruction the gradient-based algorithm is used. The reconstruction is tested considering different percentage of the pixels as damaged (missing).

关键词： compressive sensing gradient-based algorithm iris recognition

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A modified gradient-based algorithm for solving extended Sylvester-conjugate matrix equations

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ASIAN JOURNAL OF CONTROL 2018年第1期20卷 228-235页

作者： Ramadan, Mohamed A. Bayoumi, Ahmed M. E. Menoufia Univ Dept Math Fac Sci Shibin Al Kawm Egypt Ain Shams Univ Fac Educ Dept Math Cairo Egypt

In this paper, we present a modified gradient-based algorithm for solving extended Sylvester-conjugate matrix equations. The idea is from the gradient-based method introduced in [14] and the relaxed gradient-based algorithm proposed in [16]. The convergence analysis of the algorithm is investigated. We show that the iterative solution converges to the exact solution for any initial value based on some appropriate assumptions. A numerical example is given to illustrate the effectiveness of the proposed method and to test its efficiency and accuracy compared with those presented in [14] and [16].

关键词： extended Sylvester relaxation parameters gradient-based algorithm modified gradient

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Assessment of gradient-based algorithm for Surface Determination in Multi-Material Gap Measurements by X ray Computed Tomography

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MATERIALS 2020年第24期13卷 5650页

作者： Jimenez-Pacheco, Roberto Ontiveros, Sinue Yague-Fabra, Jose A. Zanini, Filippo Carmignato, Simone Albajez, Jose Antonio Ctr Univ Def AGM Carretera Huesca S-N Zaragoza 50090 Spain Autonomous Univ Baja California Dept Ind Engn Mexicali 21100 Baja California Mexico Univ Zaragoza I3A Maria de Luna 3 Zaragoza 50018 Spain Univ Padua Dept Management & Engn DTG Stradella San Nicola 3 I-36100 Vicenza Italy

X-ray computed tomography is one of the most promising measurement techniques for the dimensional evaluation of industrial components. However, the inherent complexity of this technology also involves important challenges. One of them is to develop surface determination algorithms capable of providing measurement results with better accuracy in any situation-for example, for single and multi-material parts, inner and outer geometries, with and without image artefacts, etc.-and reducing user influence. The surface determination is particularly complex in the case of multi-material parts, especially when they are separated by small air gaps. In previous works, two gradient-based algorithms were presented, that showed less measurement variability throughout the whole part, and reduced the computational cost and operator influence compared to threshold-based algorithms. This work focuses on the evaluation of the performance of these algorithms when used in a scenario so complex that parts of it are made of one or more materials (metal-metal and polymer-metal) with gaps inside. For this purpose, a set of multi-material reference standards is used. The presented gradient-based algorithms show measurement errors comparable to commercial threshold-based algorithms, but with the capability of obtaining accurate measurements in smaller gaps, apart from reducing the user influence on the measurement process.

关键词： computed tomography multi-material measurements gap measurements surface determination algorithm gradient-based algorithm

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A gradient-based algorithm for non-smooth constrained optimization problems governed by discrete-time nonlinear equations with application to long-term hydrothermal optimal scheduling control

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2022年 412卷

作者： Wu, Xiang Zhang, Kanjian Cheng, Ming Guizhou Normal Univ Sch Math Sci Guiyang 550001 Peoples R China Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China Southeast Univ Key Lab Measurement & Control CSE Minist Educ Nanjing 210096 Peoples R China

This paper considers a class of non-smooth constrained optimization problems governed by discrete-time nonlinear equations. In these problems, the non-smooth feature comes from the objective function. Our main contributions are as follows. Firstly, by using a smoothing method, the objective function can be approximated by a smooth function, which leads to an approximate optimization problem. Then, based on the idea of l1 penalty function, the state and control constraints are appended to the objective function to form an augmented objective function, which leads to a smooth unconstrained optimization problem. Next, a gradient-based algorithm with a novel line search is proposed for solving this smooth unconstrained optimization problem, and this line search is proved to have a good property similar to the Armijo line search. This is helpful to easily establish convergence results of the proposed algorithm under several mild assumptions. Finally, the proposed algorithm is adopted to solve a long-term hydrothermal optimal scheduling problem, the numerical results show that the proposed algorithm is effective, and the parameter sensitivity analysis results show that the proposed algorithm is also robust.

关键词： Non-smooth optimization Discrete-time nonlinear equation gradient-based algorithm Long-term scheduling Sensitivity analysis

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Enhancing Power System Performance via TCSC Technology Allocation With Enhanced gradient-based Optimization algorithm

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IEEE ACCESS 2024年 12卷 97806-97832页

作者： Aljumah, Ali S. Alqahtani, Mohammed H. Shaheen, Abdullah M. Elsayed, Abdallah M. Prince Sattam Bin Abdulaziz Univ Coll Engn Dept Elect Engn Al Kharj 16278 Saudi Arabia Suez Univ Fac Engn Dept Elect Engn Suez 43221 Egypt Damietta Univ Fac Engn Elect Engn Dept Dumyat 34517 Egypt

This paper addresses the critical challenge of optimal allocation of Thyristor-Controlled Series Compensator (TCSC) devices in transmission power systems through an innovative optimization framework. Leveraging an Enhanced gradient-based algorithm (EGBA) augmented with a crossover operator, the proposed methodology seeks to promote diversity in the solutions generated in each iteration, aiming to maximize the efficiency of power transmission networks. The algorithm incorporates key components such as the gradient Search Process (GSP) and Local Escaping Process (LEP) to guide the exploration process and prevent premature convergence to suboptimal solutions. Additionally, the crossover operator, a novel addition in the EGBA, facilitates the exchange of TCSC configurations between solutions, contributing to solution diversity and potentially revealing novel optimal allocations. Initially, the EGBA and GBA performances are estimated using the CEC 2017 benchmarks. Moreover, to assess the practical applicability of the suggested EGBA, it is specifically tailored and implemented to enhance the operation of transmission power systems. The primary objective is to minimize technical power losses, considering varying numbers of TCSC devices with experimentation on two distinct IEEE power systems, one with 30 buses and another with 57 buses. The results are analyzed to validate the ability of the EGBA method in optimizing power systems and addressing technical losses. The novel proposed EGBA method significantly reduces power losses compared to the original GBA method in both tested power systems. In the first system, the EGBA achieved 0.85%, 2.99%, and 1.32% lower losses than the GBA when optimizing for one, two, and three TCSC devices, respectively. In addition, the objective of enhancing the security margin of the transmission lines is involved to optimize the power flow besides the minimization function of power losses. Similarly, in the second system, the EGBA outperformed

关键词： TCSC technology TCSC allocation optimization gradient-based algorithm CEC 2017 benchmarks transmission systems TCSC technology TCSC allocation optimization gradient-based algorithm CEC 2017 benchmarks transmission systems

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An accelerated gradient-based iterative algorithm for solving extended Sylvester-conjugate matrix equations

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2018年第1期40卷 341-347页

作者： Bayoumi, Ahmed M. E. Ramadan, Mohamed A. Ain Shams Univ Fac Educ Dept Math Cairo 11566 Egypt Menoufia Univ Fac Sci Dept Math Shibin Al Kawm Egypt

In this paper, we present an accelerated gradient-based iterative algorithm for solving extended Sylvester-conjugate matrix equations. The idea is from the gradient-based method introduced in Wu et al. (Applied Mathematics and Computation 217(1): 130-142, 2010a) and the relaxed gradient-based algorithm proposed in Ramadan et al. (Asian Journal of Control 16(5): 1-8, 2014) and the modified gradient-based algorithm proposed in Bayoumi (PhD thesis, Ain Shams University, 2014). The convergence analysis of the algorithm is investigated. We show that the iterative solution converges to the exact solution for any initial value provided some appropriate assumptions be made. A numerical example is given to illustrate the effectiveness of the proposed method and to test its efficiency and accuracy compared with an existing one presented in Wu et al. (2010a), Ramadan et al. (2014) and Bayoumi (2014).

关键词： Convergence extended Sylvester-conjugate matrix equations Frobenius norm gradient-based algorithm modified gradient relaxation parameters

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