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10th International Conference on Information Optics and Photonics

作者： Lan, Zitong Zhang, Qi Xin, Xiangjun Tian, Qinghua Tao, Ying Shen, Yufei Cao, Guixing Liu, Naijing Qian, Jixi Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Beijing Key Lab Space Ground Interconnect & Conve Beijing 100876 Peoples R China

ISBN: (纸本)9781510625808

In order to solve the analog-to-digital converter (ADC) sampling rate in the traditional digital predistortion (DPD) system must be several times the bandwidth of the original signal to cover the out-of-band intermodulation components caused by nonlinear radio frequency power amplifiers (PA), low-cost ADC cannot meet today's demand problems. This paper proposes a robust iterative DPD coefficient extraction algorithm based on powell algorithm and random demodulation. This method applies an improved powell algorithm to a DPD parameter extraction system. The simulation studies the linearization performance of the system. The simulation show that when the system feedback bandwidth is equal to the original signal bandwidth, satisfactory linearization performance can be obtained. In addition, different from LM algorithm, powell algorithm does not require partial derivatives of the estimated parameters, the system is simplified.

关键词： Times Roman image area acronyms references DPD Random demodulation powell algorithm

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Sonar Image Registration Based on Improved PSO and powell Hybrid algorithm

Sonar Image Registration Based on Improved PSO and Powell Hy...

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2nd International Conference on Mechatronics and Intelligent Materials (MIM 2012)

作者： Wang, Da Bian, Hongyu Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

ISBN: (纸本)9783037853849

In order to further improve the accuracy of the sonar image registration, a novel hybrid algorithm was proposed. It proposed the normalized mutual information as similar estimation, drawn on multi-resolution data structure based on wavelet transform, a low precision solution was solved by improved PSO algorithm, which has strong global search capability, firstly and then a high precision solution was acquired by powell method, which has strong local search capability. The hybrid algorithm is effective to overcome the fall of local maximum mutual information function;it also improves solution's precision. Since the hybrid algorithm is the initial point of pre-treatment, an effective solution to the powell method dependence on the initial point. Experiments reveal that the hybrid algorithm is efficiency and effectiveness.

关键词： Image Registration PSO algorithm powell algorithm Mutual Information Sonar Images

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Fast blind beamforming method based on the powell algorithm

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Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology 2007年第8期29卷 117-120页

作者： Li, Jia-Jing Jin, Rong-Hong Geng, Jun-Ping Department of Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China

A fast blind beamforming algorithm based on the powell algorithm for maximization of the array output power was presented. Through detecting the array output, the conjugate searching directions for the optimum weight were determined. The phase of each element was shifted thus a beam was formed towards the desired user. Simulation results show that the proposed algorithm enhances the stability of beamforming and immensely reduces the computational load compared with available methods in literatures. Furthermore, it leads to a better beampattem with fewer requirements on the convergence criteria. The round of iterations and multiplications by this method is approximately 10% of the relevant methods.

关键词： Array output power Beamforming powell algorithm Smart antennas

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An algorithm Multi-Resolution Medical Image Registration Based on Firefly algorithm and powell

An Algorithm Multi-Resolution Medical Image Registration Bas...

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3rd International Conference on Intelligent System Design and Engineering Applications (ISDEA)

作者： Du Xiaogang Dang Jianwu Wang Yangping Liu Xinguo Li Sha Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Peoples R China Chinese Acad Sci Inst Modern Phys Lanzhou 730000 Peoples R China Lanzhou Gen Hosp Lanzhou Command Dept Radiotherapy Oncol Lanzhou 730050 Peoples R China

ISBN: (纸本)9780769549231;9781467348935

In order to solve the problem that the mutual information function is easy to fall into local optimal values because of much local extremism in the mutual information registration method, a multi-resolution medical image registration algorithm based on firefly algorithm and powell is put forward in this paper. The normalized mutual information is used as the similarity measure in the algorithm, and the multi-resolution strategy based on wavelet transformation is adopted in the process of searching the best value. In the lower resolution image, the firefly algorithm is used for the imprecise registration result, And in the higher resolution image, the powell algorithm is adopted for the better registration result. The experimental results show that this algorithm can effectively overcome the problem that the mutual information function is easy to get into local optimal values and improve the precision of registration result obviously.

关键词： Image registration Mutual information Firefly algorithm powell algorithm

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Application of powell Fruit Fly Optimization algorithm to Solutions of Nonlinear Equations 13

Application of Powell Fruit Fly Optimization Algorithm to So...

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13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Tang, Ye Zhou, Wei Peng, Xuyu Zunyi Normal Coll Dept Informat Engn Zunyi 563006 Guizhou Peoples R China 2 Middle Sch Huaihua 418200 Hunan Peoples R China Zunyi Normal Coll Dept Comp Sci Zunyi 563006 Guizhou Peoples R China

ISBN: (纸本)9781538621653

Solution to nonlinear equations is with extensive practical meanings in engineering. The convergence of classic numerical solutions is dependent on the initial value which is actually hard to be determined in actual computation. Thus, a new solution to nonlinear equations called PFOA is put forward to turn the complicated solution to nonlinear equations to function optimization. Group search and global convergence of the fruit fly optimization algorithm (FOA) can be fully utilized via PFOA, thereby effectively overcoming the initial point sensitivity of powell. However, positive local optimal solution can be realized by powell, so the two algorithms are improved effectively along with integration and complementation in this paper. Five typical nonlinear equations are selected, and the calculation results show the designed PFOA is superior to the basic FOA and is considered a successful solution to nonlinear equations.

关键词： Nonlinear equations powell algorithm FOA optimization simulation experiment

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powell-Based Bat algorithm for Solving Nonlinear Equations 14th

Powell-Based Bat Algorithm for Solving Nonlinear Equations

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14th International Conference on Intelligent Computing (ICIC)

作者： Ge, Gengyu Pu, Yuanyuan Zhang, Jiyuan Ouyang, Aijia Zunyi Normal Univ Sch Informat Engn Zunyi 563006 Guizhou Peoples R China

ISBN: (纸本)9783319959573;9783319959566

As the bat algorithm (BA) has defects such as slow convergence and poor calculation precision, it is likely to result in local extremum, and powell algorithm (PA) is sensitive to the initial value. To resolve the above defects, advantages and disadvantages of PA and bat algorithm are combined in this paper to solve nonlinear equations. The hybrid powell bat algorithm (PBA) not only has strong overall search ability like bat algorithm, but also has fine local search ability like powell algorithm. Experimental results show that the hybrid algorithm can be used to calculate solutions to various nonlinear equations with high precision and fast convergence. Thus, it can be considered a positive method to solve nonlinear equations.

关键词： Bat algorithm powell algorithm Hybrid algorithm Nonlinear equations Optimization

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An Optimized Knife-edge Method for On-orbit MTF Estimation of Optical Sensors using powell Parameter Fitting 11

An Optimized Knife-edge Method for On-orbit MTF Estimation o...

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Conference on Optics and Photonics for Information Processing XI

作者： Han, Lu Gao, Kun Gong, Chen Zhu, Zhenyu Guo, Yue Beijing Inst Technol Key Lab Photoelect Imaging Technol & Syst Minist Educ China Beijing 100081 Peoples R China

ISBN: (纸本)9781510612488;9781510612471

On-orbit Modulation Transfer Function (MTF) is an important indicator to evaluate the performance of the optical remote sensors in a satellite. There are many methods to estimate MTF, such as pinhole method, slit method and so on. Among them, knife-edge method is quite efficient, easy-to-use and recommended in ISO12233 standard for the whole-frequency MTF curve acquisition. However, the accuracy of the algorithm is affected by Edge Spread Function (ESF) fitting accuracy significantly, which limits the range of application. So in this paper, an optimized knife-edge method using powell algorithm is proposed to improve the ESF fitting precision. Fermi function model is the most popular ESF fitting model, yet it is vulnerable to the initial values of the parameters. Considering the characteristics of simple and fast convergence, powell algorithm is applied to fit the accurate parameters adaptively with the insensitivity to the initial parameters. Numerical simulation results reveal the accuracy and robustness of the optimized algorithm under different SNR, edge direction and leaning angles conditions. Experimental results using images of the camera in ZY-3 satellite show that this method is more accurate than the standard knife-edge method of ISO12233 in MTF estimation.

关键词： MTF ESF knife-edge method powell algorithm

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Combining Support Vector Machines and Markov Random Fields in an Integrated Framework for Contextual Image Classification

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2013年第5期51卷 2734-2752页

作者： Moser, Gabriele Serpico, Sebastiano B. Univ Genoa Dept Telecommun Elect Elect & Naval Engn DITEN I-16145 Genoa Italy

In the framework of remote-sensing image classification, support vector machines (SVMs) have lately been receiving substantial attention due to their accurate results in many applications as well as their remarkable generalization capability even with high-dimensional input data. However, SVM classifiers are intrinsically noncontextual, which represents an important limitation in image classification. In this paper, a novel and rigorous framework, which integrates SVMs and Markov random field models in a unique formulation for spatial contextual classification, is proposed. The developed contextual generalization of SVMs, is obtained by analytically relating the Markovian minimum-energy criterion to the application of an SVM in a suitably transformed space. Furthermore, as a second contribution, a novel contextual classifier is developed in the proposed general framework. Two specific algorithms, based on the Ho-Kashyap and powell numerical procedures, are combined with this classifier to automate the estimation of its parameters. Experiments are carried out with hyperspectral, multichannel synthetic aperture radar, and multispectral high-resolution images and the behavior of the method as a function of the training-set size is assessed.

关键词： Contextual image classification Ho-Kashyap algorithm Markov random fields powell algorithm span bound support vector machines (SVMs)

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algorithmic Optimization of Transistors Applied to Silicon LDMOS

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IEEE ACCESS 2023年 11卷 64160-64169页

作者： Chuang, Ping-Ju Saadat, Ali van de Put, Maarten L. L. Edwards, Hal Vandenberghe, William G. G. Univ Texas Dallas Dept Mat Sci & Engn Richardson TX 75080 USA Texas Instruments Inc Kilby Labs Santa Clara CA 95051 USA Interuniv Microelect Ctr IMEC B-3001 Leuven Belgium Texas Instruments Inc Analog Technol Dev Dallas TX 75243 USA

We propose a pioneering approach that integrates optimization algorithms and technology computer-aided design to automatically optimize laterally-diffused metal-oxide-semiconductors (LDMOS) with a field-oxide structure. We define the ratio of the square of the breakdown voltage divided by the specific on-resistance as the figure-of-merit (FOM) and the objective function of our optimization. We compare the performance of three different algorithms: Nelder-Mead, powell, and Bayesian Optimization. We show how the LDMOS performance evolves as each of the three optimization algorithms reach their optimized structure. We show that a straightforward Nelder-Mead optimization leads to a local optimum when optimizing over six input parameters. We find that Bayesian Optimization is the most data-efficient method to find the global optimized structure in the multi-domain design space.

关键词： Bayesian optimization LDMOS nelder-mead algorithm power semiconductor device powell algorithm step gate field oxide structure

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OPTIMIZATION TECHNIQUES IN ENERGY CALCULATIONS INVOLVING THE HARTREE-FOCK DENSITY-MATRIX

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1993年第2期76卷 225-240页

作者： WAGGONER, CA COMBS, LL MISSISSIPPI STATE UNIV DEPT CHEMMISSISSIPPI STATEMS 39762

Three optimization procedures are examined for their utilization in determining the optimum density matrix for a single determinant wave function. The total energy of a molecular system is written as a function of the density matrix and then optimized subject to the constraints of idempotency and total electron population. This direct calculation of the density matrix (DCDM) method was studied in an attempt to have a formalism which would avoid convergence problems associated with the self-consistent field (SCF) cycle, and which would be applicable to large molecular systems. The optimization procedures studied were the powell algorithm, Gauss-Jordan reduction, and dynamic programming. Computational factors studied include convergence criteria, stepsize, and weight factors for constraint equation penalty functions. The application considered is for HF. An ab-initio SCF method was used to obtain initial values for the density matrix, and its SCF results were compared to corresponding DCDM predictions. Approximations of the quadratic two-electron energy contributions will be necessary to apply dynamic programming, but this appears to be the method most applicable to large molecular systems if an acceptable approximation can be found. Gauss-Jordan reduction is an applicable technique, but probably not for large molecular systems. BOTM appears to be the method most applicable without introducing approximations, but weight factors for the penalty functions will have to be more efficiently determined as Lagrange multipliers, and this addition would result in a technique probably not applicable to large molecular systems.

关键词： DENSITY MATRIX HARTREE-FOCK DENSITY MATRIX powell algorithm GAUSS-JORDAN REDUCTION DYNAMIC PROGRAMMING

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