Sharif Digital Repository

This letter presents a fast microwave imaging technique based on the concept of smoothed minimization and adaptive thresholding. The distorted Born iterative method (DBIM) is used to solve the electromagnetic (EM) inverse scattering problem. We propose to solve the set of underdetermined equations at each iteration of the DBIM algorithm using an L2 regularized iterative smoothed adaptive thresholding (L2-ISATCS) technique. Our simulation results confirm that this technique can reduce considerably the required reconstruction times for the DBIM method relative to previously suggested compressed sensing (CS)-based approaches  

We propose a new inverse scattering technique based on sparsity for the application of microwave imaging. The underdetermined inverse problem appeared in the distorted born iterative method (DBIM) technique is solved using the suggested L2-regularized iterative weighted algorithm (L2-IWA). The L2-regularizer has been introduced to stabilize the algorithm against nonlinear approximations, and the sparsity is enforced with the aid of another reweighted L2-norm regularizer to address the ill-posedness of the inverse problem. The derived algorithm is a three-step iterative technique which solves the underdetermined set of equations at each DBIM iteration. Moreover, the convergence of the L2-IWA... 

In this paper, we propose an algorithm for recovery of sparse and low-rank components of matrices using an iterative method with adaptive thresholding. In each iteration of the algorithm, the low-rank and sparse components are obtained using a thresholding operator. The proposed algorithm is fast and can be implemented easily. We compare it with the state-of-the-art algorithms. We also apply it to some applications such as background modeling in video sequences, removing shadows and specularities from face images, and image restoration. The simulation results show that the proposed algorithm has a suitable performance with low run-time. © 2017 Elsevier Inc  

Reconstructing a signal corrupted by impulsive noise is of high importance in several applications, including impulsive noise removal from images, audios and videos, and separating texts from images. Investigating this problem, in this paper we propose a new method to reconstruct a noise-corrupted signal where both signal and noise are sparse but in different domains. We apply our algorithm for impulsive noise (Salt- and-Pepper Noise (SPN) and Random-Valued Impulsive Noise (RVIN) removal from images and compare our results with other notable algorithms in the literature. Simulation indicates show that our algorithm is not only simple and fast, but also it outperforms the other... 

The effective utilization of the spectrum has become an essential goal in the communications field, which is addressed by the Cognitive Radio (CR) systems. The primary task in a CR system is to sense the spectrum to identify its holes to be exploited by the secondary users. In this paper, we tackle the compressed spectrum sensing problem in a cooperative manner. The CRs distributed in an area take the samples of the signal that has been reached to them through a wireless fading channel. The spectrum has the block-sparse structure. Moreover, the spectrum observed by different CRs in an area share the same block-sparse support. Therefore, we suggest to exploit the joint block-sparsity... 

A cosmic ray telescope consisting of two scintillators (each one with a surface area of 0.14 m2, spaced 283 cm top of each other) was constructed to study the angular distribution of atmospheric muons. Using the CORSIKA code, the muons energy spectrum is parameterized in different energy regions at Tehran's altitude (1200 m above sea level ≡897 gcm−2), and by using a Monte Carlo program, the minimum energy recorded by the telescope is calculated. Due to the geomagnetic field, in the azimuth angle distribution of atmospheric muons, an anisotropy is observed in the East–West direction. The zenith angle distribution of the atmospheric muons follows the function cosnθ. Due to the relatively... 

Iterative methods have led to better understanding and solving problems such as missing sampling, deconvolution, inverse systems, and impulsive and Salt and Pepper noise removal problems. However, the challenges regarding the speed of convergence and or the accuracy of the answer still remain. In order to improve the existing iterative algorithms, a non-linear method is discussed in this paper. The mentioned method is analyzed from different aspects, including its convergence and its ability to accelerate recursive algorithms. We show that this method is capable of improving Iterative Method (IM) as a non-uniform sampling reconstruction algorithm and some other iterative sparse recovery... 

The Block method approach to solve EIT problem leads to an exact solution if the measurements are done without error. Non-iterative method is a feasible approach on solving 3D EIT forward problem. However, the effect of the measurement error has not been considered in this method yet. In this article, the 3D model of EIT with block method has been considered. The required equations to solve the forward problem are then generated. To solve the forward problem, non-iterative method has been employed. Effect of the measurement error on forward problem for a 3D model of EIT are generated. It has been shown that for a sample 3D model, measurement error can propagate exponentially. ©2007 IEEE  

A morphing-body optimization method is introduced to accelerate adjoint-based shape optimization techniques. The optimization process solves the flow and adjoint equations around a continuously deforming body whose shape is controlled by the cost function. Effect of various parameters on the efficiency of the scheme is studied. It is found that, for the best performance of the algorithm, the morphing rate of the airfoil should be restricted, since larger rates foster oscillations and lower values are not computationally feasible. Moreover, the iterative procedure in the adjoint solver should be adapted to the iteration scheme in the flow solver and to the morphing rate  

In this paper we propose a new method to recover bandlimited signals corrupted by impulsive noise. The proposed method uses CFAR adaptive thresholding and soft decision making to detect the locations of the impulsive noise. Then an iterative method cancels noise and reconstructs the signal. This estimate in turn will be used to make the approximation of the impulsive noise more accurate. Simulation results confirm the robustness of the proposed algorithm even when impulsive noise exceeds the theoretical reconstruction capacity. ©2008 IEEE  

The objective of this article is to study the performance of iterative parameter and function estimation techniques to solve simultaneously two unknown functions (quadratic in time, and linear in time and space) using transient inverse heat conduction method in conjunction with a geometrical domain decomposition approach, in cylindrical coordinates. For geometrical decomposition of physical domain, a multi-block method has been used. The numerical scheme for the solution of the governing partial differential equations is the finite element method. The results of the present study for a configuration composed of two joined disks with different heights are compared to those of exact heat... 

In this paper, a parallel algorithm for computing the roots of a given polynomial of degree n on a ring of processors is proposed. The algorithm implements Durand-Kerner's method and consists of two phases: initialisation, and iteration. In the initialisation phase all the necessary preparation steps are realised to start the parallel computation. It includes register initialisation and initial approximation of roots requiring 3n - 2 communications, 2 exponentiation, one multiplications, 6 divisions, and 4n - 3 additions. In the iteration phase, these initial approximated roots are corrected repeatedly and converge to their accurate values. The iteration phase is composed of some iteration... 

The ABS methods, introduced by Abaffy, Broyden and Spedicato, are direct iteration methods for solving a linear system where the ith iterate satisfies the first i equations, therefore a system of m equations is solved in at most m steps. Recently, we have presented a new approach to devise a class of ABS-type methods for solving full row rank systems [K. Amini, N. Mahdavi-Amiri, M. R. Peyghami, ABS-type methods for solving full row rank linear systems using a new rank two update, Bulletin of the Australian Mathematical Society 69 (2004) 17-31], the ith iterate of which solves the first 2i equations. Here, to reduce the space and computation time, we use a new extended rank two update formula... 

In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and X iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods. © 2006 IEEE  

Salahi et al. [M. Salahi, J. Peng, T. Terlaky, On Mehrtora type predictor-corrector algorithms, Technical Report 2005/4, Advanced Optimization Lab, Department of Computing and Software, McMaster University, http://www.cas.mcmaster.ca/~oplab/publication, SIAM Journal on Optimization, submitted for publication] give a numerical example showing that Mehrotra's original predictor-corrector algorithm, which is the basis of interior point methods software packages, may be very inefficient in practice. This motivated Salahi et al. to come up with a safeguarded algorithm that enjoys a polynomial iteration complexity and is efficient in practice. Here we discuss a variation of Mehrotra's second order... 

In building energy simulation, an integrated modelling of airflow in the building needed. Therefore, in this paper two approaches are used for building energy simulation: zonal network for modelling of the building segments and Computational Fluid Dynamics (CFD) for modelling of the airflow. It is noted that a synchronize solution process is needed for the building and the CFD equation-sets. For this purpose an iterative procedure is used to corresponding solution of these equations. © 2005 Elsevier Ltd. All rights reserved  

Coordination strategies in large-scale systems are mainly based on two principles; Interaction Prediction Principle and Interaction Balance Principle. In this paper, which consists of two parts, the concept of coordination is introduced within the framework of two-level large-scale systems, and two new approaches for coordination based on Interaction Prediction Principle and Interaction Balance Principle have been presented. The new strategies have much faster convergence rate than the previously suggested classical methods. They extremely reduce the number of iterations required for obtaining the overall optimal solutions. The efficacy and advantage of the proposed approaches, in compare to... 

In this paper, the parallel implementations of different iterative polynomial root finding methods on a processor with SIMD processing capability are reported. These methods are based on the construction of a sequence of approximations that converge to the set of roots. We have chosen four widely used methods namely Newton's, Durand-Kerner's, Aberth-Ehrlich's, and QD and implemented them using the SIMD instruction set of the Pentium processor with C++ and assembly language. Experiments show that a speedup of 3 or higher can be achieved, depending on the order of polynomial, required accuracy, and the method employed. © 2005 IEEE  

Conventional features for speech recognition have not been evaluated in terms of importance in human speech recognition. In this paper a method for extracting important features in an interactive process has been introduced. This method can be used as an aid for experts in an ASR expert system. It has also been shown, as an application of our method, how an expert might find out the distinguishing features between "m" and "n". As another use, it has been illustrated that how our method could be used to check the sufficiency of information in the quantized filter-bank for speech recognition