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13rd IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Zou, Yanbin Zhang, Zekai Liu, Huaping Shantou Univ Dept EE Shantou Guangdong Peoples R China Oregon State Univ Sch EECS Corvallis OR 97331 USA

ISBN: (纸本)9798350344820;9798350344813

Non-line-of-sight (NLOS) propagation could severely degrade the performance of wireless localization systems. Thus, algorithms that are robust to NLOS error are valuable. In this paper, based on hybrid angle-of-arrival (AOA) and time-of-arrival (TOA) measurements, we propose a localization approach that is robust against NLOS errors. It starts with a modified maximum likelihood estimation (MLE) problem, where range NLOS errors and angle NLOS errors are included in the objective function. Then three observations are exploited to develop an effective iteration algorithm: 1) the range NLOS error is always positive;2) the angle NLOS error could be either positive or negative, making it more difficult to address than range NLOS errors;3) the angle NLOS error is highly correlated with the range NLOS error for each link. In the iterative process, range NLOS errors, the weight matrix of the weighted least-squares (WLS) formulated from AOA measurements, and the source location are alternatively updated. The performance of the proposed algorithm is compared with that of existing methods in simulation.

关键词： Source localization iterative algorithm non-line-of-sight (NLOS) time-of-arrival (TOA) angle-of-arrival (AOA)

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On the regularized Lagrange principle in iterative form and its application for solving unstable problems

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Mathematical Models and Computer Simulations 2017年第3期9卷 328-338页

作者： Kuterin, F.A. Sumin, M.I. Lobachevsky State University Nizhny Novgorod Russian Federation

For a convex programming problem in a Hilbert space with operator equality constraints, the Lagrange principle in sequential nondifferential form or, in other words, the regularized Lagrange principle in iterative form, that is resistant to input data errors is proved. The possibility of its applicability for direct solving unstable inverse problems is discussed. As an example of such problem, we consider the problem of finding the normal solution of the Fredholm integral equation of the first kind. The results of the numerical calculations are shown. © 2017, Pleiades Publishing, Ltd.

关键词： dual regularization duality instability iterative algorithm Kuhn–Tucker theorem Lagrange principle sequential optimization solving unstable problems

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An Efficient iterative Method for Extracting Parameters of Photovoltaic Panels with Single Diode Model 5

An Efficient Iterative Method for Extracting Parameters of P...

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5th International Conference on Renewable Energy for Developing Countries (REDEC)

作者： Benahmida, Ahdelaaziz Maouhoub, Noureddine Sahsah, Hassan Ibn Zohr Univ Fac Sci Dept Phys Lab Metrol & Informat Proc BP 8106 Agadir Morocco Ibn Zohr Univ Fac Sci Dept Phys Lab Elect Signal Proc & Phys Modeling BP 8106 Agadir Morocco

ISBN: (纸本)9781728155951

In this paper, a five parameter extraction method for a single diode model of photovoltaic panels is proposed. The method is based on an iterative algorithm and able to estimate the electrical parameters from the panel's datasheet information. Three steps are used to extract the five single diode model parameters. In the first step, we estimate analytically the ideality factor using the different information from the panel's datasheet. In the second step, we formulate three analytical equations that permit us to find the parallel resistance, the saturation current and the photo-current as function of the series resistance and the ideality factors. The third step allows us to determine the optimal value of the series resistance using an iterative procedure that minimizes the error between the theoretical and the experimental maximum power values. The proposed method is applied to the polycrystalline silicon photovoltaic KC200GT solar module under standard test conditions (STC) and under different irradiations and temperatures. The results show a good agreement between the simulated data and the experimental measure extracted from datasheet.

关键词： iterative algorithm Newton Raphson method Parameters extraction Photovoltaic (PV) Single-diode model

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European day-ahead market clearing model incorporating linearized AC power flow constraints 19

European day-ahead market clearing model incorporating linea...

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19th Power Systems Computation Conference (PSCC)

作者： Dourbois, Grigoris A. Biskas, Pandelis N. Chatzigiannis, Dimitris I. Vlachos, Andreas G. Bakirtzis, Anastasios G. Aristotle Univ Thessaloniki Dept Elect & Comp Engn Power Syst Lab Thessaloniki Greece

ISBN: (纸本)9788894105124

A model for the solution of a European-type day-ahead market with multi-period products is presented in this paper, though considering a nodal network representation and including N and N-1 transmission security constraints. An iterative process is employed, similar to the process implemented in the U.S. markets, coordinating a market clearing problem (formulated as a Mixed Integer Linear Programming-MIP model) with an AC load flow solution, in order to check the apparent power flows of transmission lines against their respective limits, accounting the influence of voltage magnitudes and reactive power on the system lines' power flows. A distributed-slack modelling is used, in order to ensure the robustness of the attained Locational Marginal Prices, so that they are independent of the selection of the system reference node. The model is evaluated in terms of pricing and computational efficiency using the Balkan nodal power system.

关键词： locational marginal prices multi-period products AC load flow apparent power Line Outage Distribution Factors iterative algorithm

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A new approach of blind image restoration

A new approach of blind image restoration

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IEEE International Conference on Systems, Man and Cybernetics (SMC 03)

作者： Jin, C Chen, C Bu, JJ Zhejiang Univ Coll Comp Sci Hangzhou 310027 Peoples R China

ISBN: (纸本)0780379527

Blurring is inevitable in many image acquisition systems. Blind image restoration is one of deblur methods, and because it does not need a priori point spread function (PSF), it becomes more and more popular. In this paper, a novel method of blind image restoration is presented which can be applied to various kinds of images. The method has no limitation on blurred images, and does not need any extra database supports. Gaussian Blur is assumed to be able to present every other blur, and by successfully dealing with Gaussian Blur, our method can be suitable to deal with other blur methods. In order to reduce the noise, a pre-processing step is introduced. With edge detection, point spread function can be reconstructed automatically. Then an iterative algorithm is used to restore the image. Experimental results show the good performance of this method.

关键词： blind image restoration Gaussian blur PSF reconstruction iterative algorithm

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Improving the accuracy of 3D surface reconstruction by controlling height compensation 6

Improving the accuracy of 3D surface reconstruction by contr...

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6th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Gao, Xu Guo, Peiji Soochow Univ Educ Minist China Key Lab Adv Opt Mfg Technol Jiangsu Prov Sch Optoelect Sci & Engn Suzhou 215006 Jiangsu Peoples R China Soochow Univ Educ Minist China Key Lab Modern Opt Technol Suzhou 215006 Jiangsu Peoples R China

ISBN: (纸本)9781510637054

The southwell model algorithm based on the least squares method is suitable for a variety of wavefront reconstruction and three-dimensional shape detection through slope fitting. Due to the assumption that the height is linearly related to the gradient in the southwell model, the detailed infoimation of the surface shape needs to be gradually improved by the iterative algorithm. In this paper, we add an attenuation factor in the foul' of a power function controlled by exponential and iterative times to increase the height compensation amount in the early iteration and control the excessive noise data to participate in the iteration, which leads to the deviation of the fitted surface shape from the actual surface shape. Through simulation comparison experiments, the new algorithm has faster iteration rate and higher accuracy than traditional iterative algorithms.

关键词： southwell model wavefront reconstruction iterative algorithm height compensation

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UAV-Assisted Data Rate Maximization Under 3-D Channel Model 93

UAV-Assisted Data Rate Maximization Under 3-D Channel Model

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IEEE 93rd Vehicular Technology Conference (VTC-Spring)

作者： Lin, Jianzhen Pan, Cunhua He, Chunlong Wang, Kezhi Shenzhen Univ Guangdong Key Lab Intelligent Informat Proc Shenzhen Peoples R China Queen Mary Univ London Sch Elect Engn & Comp Sci London England Northumbria Univ Dept Comp & Informat Sci Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781728189642

This paper investigates a UAV-enabled wireless downlink system, where a UAV-enabled base station flies above a group of Internet of things devices (IoTDs) and transmits data to them. In order to ensure the fairness among all IoTDs, we jointly optimize scheduling association and UAV trajectory to maximize the minimal throughput of all IoTDs under the 3-dimensional (3-D) channel model. Meanwhile, to ensure the stability of communication, we aim to guarantee a high probability of line-of-sight (LoS) links between the UAV and all IoTDs. The optimization problem is non-convex and we propose an iterative algorithm based on the block coordinate descent and successive convex approximation to solve it. Furthermore, we show the convergence of the algorithm through simulations. It is shown that the proposed algorithm achieves higher data rate than the traditional scheme without guaranteeing the LoS probability.

关键词： UAV communication trajectory iterative algorithm

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On iterative Solutions of Periodic Sylvester Matrix Equations 39

On Iterative Solutions of Periodic Sylvester Matrix Equation...

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39th Chinese Control Conference (CCC)

作者： Chen, Zebin Chen, Xuesong Guangdong Univ Technol Sch Appl Math Guangzhou 510520 Peoples R China

ISBN: (纸本)9789881563903

We propose a gradient based iterative algorithm with multiple iterative factors (MGI) to find the solutions of the Sylvester discrete-time periodic matrix equations A(j)X(j) + Xj+1Bj = C-j(j = 1,2, ... , T). It is proved that the exact solution of the periodic matrix equations can be converged by the MGI method for any initial matrices. Then, we study the optimal convergence rate of gradient based iterative algorithm with single iterative factor (SGI). Nextly, we compare the convergence rate of the two algorithms, and find that MGI is faster than SGI when the appropriate convergence factors mu(j) are selected. Finally, a numerical example is given to verify that MGI is superior to SGI in both speed and iterative steps.

关键词： iterative algorithm Multiple iterative Factors Periodic Matrix Equations Convergence Rate

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Sparsity Constrained Born Inversion for Breast Cancer Detection

Sparsity Constrained Born Inversion for Breast Cancer Detect...

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IEEE International Ultrasonics Symposium (IUS)

作者： Ramirez, Ana B. van Dongen, Koen W. A. Ind Univ Santander Sch Elect & Elect Engn Bucaramanga Colombia Delft Univ Technol Dept Imaging Phys Lab Acoust Wavefield Imaging Delft Netherlands

ISBN: (纸本)9781479981823

Ultrasound has been successfully used for detecting and characterizing small breast lesions. To improve the image quality, an imaging method known as Born inversion (BI) in combination with compressive sensing (CS) theory has been studied. BI is an iterative method which is simple and computationally efficient. However, due to the ill-posedness of the inverse problem, the resulting image will diverge from the correct solution after several iterations. In this work, we use CS ideas to (1) regularize the inversion process and (2) reduce the number of unknowns by restricting the solution of the BI method to be sparse in a wavelet domain. The sparse BI method estimates a contrast function by minimizing a cost functional given by the mean square error between the measured and modeled data. To regularize the inverse problem and to include sparseness, an extra penalty term is added to this cost functional. This penalty term defines the set of coefficients of the estimated image in the wavelet transform domain whose L-0-norm is minimal. A solution for the sparse BI method is found by using an iterative algorithm, which at each iteration first estimates a contrast function image using the conjugate gradient solution, then computes the wavelet transform of the estimated image and finally selects the wavelets with the largest coefficients. The sparse BI method has been tested successfully on noise-free and noisy synthetic data set representing a tomographic scan of a cancerous breast. Experimental results show that the sparse Born inversion method remains convergent as the number of iterations increases, in comparison to conventional BI method.

关键词： biological organs biomedical ultrasonics cancer compressed sensing conjugate gradient methods image denoising image reconstruction inverse problems iterative methods mean square error methods medical image processing ultrasonic imaging wavelet transforms breast cancer detection breast lesions compressive sensing theory conjugate gradient solution contrast function contrast function imaging image quality iterative algorithm mean square error noise-free synthetic data set noisy synthetic data set sparse BI method sparsity constrained Born inversion tomographic scan ultrasound imaging wavelet domain wavelet transform Bismuth Breast Image reconstruction Imaging iterative methods Noise measurement Wavelet transforms

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Image Restoration algorithm of Smoothness Constraints Constructed by Adaptive Fuzzy Edge Evaluation Function 7

Image Restoration Algorithm of Smoothness Constraints Constr...

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Seventh International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2015)

作者： Ping, Shi Ya Guangdong Univ Sci & Technol Dongwan 523083 Guangdong Peoples R China

ISBN: (纸本)9781467371438

Image restoration is an important research field of image processing. The purpose of image restoration is to improve the observed visual effect of image to make it close to the original image. This paper proposes an image restoration algorithm of smoothness constraints constructed by adaptive fuzzy edge evaluation function. First, image degradation/restoration model is introduced, based on the degradation function to solve the ill-posed problem of image restoration. Then, with the process of iteration, more image details can be detected, while the algorithm adaptively produces a more reasonable smoothness constraints. This algorithm can base on restricted adaptive image restoration algorithm, by increasing the sophistication of weight to improve the recovery of adaptive control capabilities. Finally, an experiment can be conducted to prove the effectiveness and feasibility of the image restoration algorithm proposed in this paper.

关键词： Image restoration Smoothness constraints Sobel approach iterative algorithm Edge detection

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