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    Analysis of large amplitude free vibrations of clamped tapered beams on a nonlinear elastic foundation

    , Article Applied Mathematical Modelling ; Volume 38, Issue 3 , 1 February , 2014 , Pages 1176-1186 ; ISSN: 0307904X Baghani, M ; Mazaheri, H ; Salarieh, H ; Sharif University of Technology
    Abstract
    The purpose of this paper is to present efficient and accurate analytical expressions for large amplitude free vibration analysis of single and double tapered beams on elastic foundation. Geometric nonlinearity is considered using the condition of inextensibility of neutral axis. Moreover, the elastic foundation consists of a linear and cubic nonlinear parts together with a shearing layer. The nonlinear governing equation is solved by employing the variational iteration method (VIM). This study shows that the second-order approximation of the VIM leads to highly accurate solutions which are valid for a wide range of vibration amplitudes. The effects of different parameters on the nonlinear... 

    Limit analysis of FGM circular plates subjected to arbitrary rotational symmetric loads using von-Mises yield criterion

    , Article Acta Mechanica ; Volume 224, Issue 8 , 2013 , Pages 1601-1608 ; 00015970 (ISSN) Baghani, M ; Fereidoonnezhad, B ; Sharif University of Technology
    2013
    Abstract
    In this paper, employing the limit analysis theorem, critical loading on functionally graded (FG) circular plate with simply supported boundary conditions and subjected to an arbitrary rotationally symmetric loading is determined. The material behavior follows a rigid-perfectly plastic model and yielding obeys the von-Mises criterion. In the homogeneous case, the highly nonlinear ordinary differential equation governing the problem is analytically solved using a variational iteration method. In other cases, numerical results are reported. Finally, the results are compared with those of the FG plate with Tresca yield criterion and also in the homogeneous case with those of employing the... 

    Iterative method for fusion of infrared and visible images

    , Article 9th International Symposium on Telecommunication, IST 2018, 17 December 2018 through 19 December 2018 ; 2019 , Pages 652-657 ; 9781538682746 (ISBN) Zamani, H ; Zarmehi, N ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    This paper proposes a novel fusion method for visible and infrared images. The infrared and visible samples are obtained by a sampling pattern such as star and spiral. Then, the samples are fused according to fusion rules. Finally, the proposed method is applied to fuse the infrared and visible samples. The proposed method is iterative and a significant advantage of it, besides its superior performance, is that it is faster than the previous compressive sensing based fusion methods. The simulation results confirm the success of the proposed method for fusion of infrared and visible images. © 2018 IEEE  

    Iteratively Constructing Preconditioners via the Conjugate Gradient Method

    , M.Sc. Thesis Sharif University of Technology Mousa Abadian, Mohammad (Author) ; Farhadi, Hamid Reza (Supervisor)
    Abstract
    The main goal of this work is solving system of linear equations Ax = b, where A is a n_n square matrix, b is a n_1 vector and x is the vector of unknowns. When n is large, using direct methods is not economical. Thus, the system is solved by iterative methods. At first, projection method onto subspace K _ Rn with dimension m _ n is described, and then this subspace K is equalized with the krylov subspace. Then,some samples of projection methods onto the krylov subspace, such as FOM, GMRES and CG (Conjugate Gradient), are considered. The preconditioning of the linear system is explained, that is, instead of solving system Ax = b, the system PAx = Pb (P nonsingular), is solved, such that the... 

    An algorithm for discovering clusters of different densities or shapes in noisy data sets

    , Article Proceedings of the ACM Symposium on Applied Computing ; March , 2013 , Pages 144-149 ; 9781450316569 (ISBN) Khani, F ; Hosseini, M. J ; Abin, A. A ; Beigy, H ; Sharif University of Technology
    2013
    Abstract
    In clustering spatial data, we are given a set of points in Rn and the objective is to find the clusters (representing spatial objects) in the set of points. Finding clusters with different shapes, sizes, and densities in data with noise and potentially outliers is a challenging task. This problem is especially studied in machine learning community and has lots of applications. We present a novel clustering technique, which can solve mentioned issues considerably. In the proposed algorithm, we let the structure of the data set itself find the clusters, this is done by having points actively send and receive feedbacks to each other. The idea of the proposed method is to transform the input... 

    Progressive sparse image sensing using Iterative Methods

    , Article 2012 6th International Symposium on Telecommunications, IST 2012 ; 2012 , Pages 897-901 ; 9781467320733 (ISBN) Azghani, M ; Marvasti, F ; Sharif University of Technology
    2012
    Abstract
    Progressive image transmission enables the receivers to reconstruct a transmitted image at various bit rates. Most of the works in this field are based on the conventional Shannon-Nyquist sampling theory. In the present work, progressive image transmission is investigated using sparse recovery of random samples. The sparse recovery methods such as Iterative Method with Adaptive Thresholding (IMAT) and Iterative IKMAX Thresholding (IKMAX) are exploited in this framework since they have the ability for successive reconstruction. The simulation results indicate that the proposed method performs well in progressive recovery. The IKMAX has better final reconstruction than IMAT at the cost of... 

    A dictionary learning method for sparse representation using a homotopy approach

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 25 August 2015 through 28 August 2015 ; Volume 9237 , August , 2015 , Pages 271-278 ; 03029743 (ISSN) ; 9783319224817 (ISBN) Niknejad, M ; Sadeghi, M ; Babaie Zadeh, M ; Rabbani, H ; Jutten, C ; Sharif University of Technology
    Springer Verlag  2015
    Abstract
    In this paper, we address the problem of dictionary learning for sparse representation. Considering the regularized form of the dictionary learning problem, we propose a method based on a homotopy approach, in which the regularization parameter is overall decreased along iterations. We estimate the value of the regularization parameter adaptively at each iteration based on the current value of the dictionary and the sparse coefficients, such that it preserves both sparse coefficients and dictionary optimality conditions. This value is, then, gradually decreased for the next iteration to follow a homotopy method. The results show that our method has faster implementation compared to recent... 

    Adaptive singular value thresholding

    , Article 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017, 3 July 2017 through 7 July 2017 ; 2017 , Pages 442-445 ; 9781538615652 (ISBN) Zarmehi, N ; Marvasti, F ; Anbarjafari, G ; Kivinukk, A ; Tamberg, G ; Sharif University of Technology
    Abstract
    In this paper, we propose an Adaptive Singular Value Thresholding (ASVT) for low rank recovery under affine constraints. Unlike previous iterative methods that the threshold level is independent of the iteration number, in our proposed method, the threshold in adaptively decreases during iterations. The simulation results reveal that we get better performance with this thresholding strategy. © 2017 IEEE  

    Bounds on discrete fourier transform of random mask

    , Article 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017, 3 July 2017 through 7 July 2017 ; 2017 , Pages 327-330 ; 9781538615652 (ISBN) Zarmehi, N ; Marvasti, F ; Anbarjafari, G ; Kivinukk, A ; Tamberg, G ; Sharif University of Technology
    Abstract
    This paper proposes some bounds on maximum of magnitude of a random mask in Fourier domain. The random mask is used in random sampling scheme. Having a bound on the maximum value of a random mask in Fourier domain is very useful for some iterative recovery methods that use thresholding operator. In this paper, we propose some different bounds and compare them with the empirical examples. © 2017 IEEE  

    A new analytical approximation to the Duffing-harmonic oscillator

    , Article Chaos, Solitons and Fractals ; Volume 42, Issue 1 , 2009 , Pages 571-576 ; 09600779 (ISSN) Fesanghary, M ; Pirbodaghi, T ; Asghari, M ; Sojoudi, H ; Sharif University of Technology
    2009
    Abstract
    In this paper, a novel analytical approximation to the nonlinear Duffing-harmonic oscillator is presented. The variational iteration method (VIM) is used to obtain some accurate analytical results for frequency. The accuracy of the results is excellent in the whole range of oscillation amplitude variations. © 2009 Elsevier Ltd. All rights reserved  

    Convergence analysis of an iterative method for the reconstruction of multi-band signals from their uniform and periodic nonuniform samples

    , Article Sampling Theory in Signal and Image Processing ; Volume 7, Issue 2 , 1 May , 2008 , Pages 113-129 ; 15306429 (ISSN) Amini, A ; Marvasti, F ; Sharif University of Technology
    2008
    Abstract
    One of the proposed methods for recovery of a band-limited signal from its samples, whether uniform or nonuniform, is the so-called Frame Method. In this method the original signal is reconstructed by iterative use of sampling-filtering blocks. Convergence of this method for linear invertible operators has been previously proved. In this paper we show that this method for non-invertible periodic nonuniform samplings as well as non-invertible uniform samples of bandpass (or multi-band) signals will lead to the pseudo-inverse solution. Convergence conditions in case of additive noise will also be discussed. © 2008 Sampling Publishing  

    Some nonlinear/adaptive methods for fast recovery of the missing samples of signals

    , Article Signal Processing ; Volume 88, Issue 3 , 2008 , Pages 624-638 ; 01651684 (ISSN) Ghandi, M ; Jahani Yekta, M. M ; Marvasti, F ; Sharif University of Technology
    2008
    Abstract
    In this paper an iterative method for recovery of the missing samples of signals is investigated in detail, and some novel linear, nonlinear, and adaptive extrapolation techniques are proposed to be used along with it to increase the convergence rate of the recovery system. The proposed methods would remarkably speed up the convergence rate, save processing power, and reduce the delay of the system compared to some well known accelerated versions of the aforementioned iterative algorithm. © 2007 Elsevier B.V. All rights reserved  

    Microwave imaging based on compressed sensing using adaptive thresholding

    , Article 8th European Conference on Antennas and Propagation, EuCAP 2014 ; 2014 , pp. 699-701 ; ISBN: 9788890701849 Azghani, M ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
    Abstract
    We propose to use a compressed sensing recovery method called IMATCS for improving the resolution in microwave imaging applications. The electromagnetic inverse scattering problem is solved using the Distorted Born Iterative Method combined with the IMATCS algorithm. This method manages to recover small targets in cases where traditional DBIM approaches fail. Furthermore, by applying an L2-based approach to regularize the sparse recovery algorithm, we improve the algorithm's robustness and demonstrate its ability to image complex breast structures. Although our simulation scenarios do not fully represent experimental or clinical data, our results suggest that the proposed algorithm may be... 

    Analytical solution for large amplitude vibrations of microbeams actuated by an electro-static force

    , Article Scientia Iranica ; Volume 20, Issue 5 , 2013 , Pages 1499-1507 ; 10263098 (ISSN) Baghani, M ; Asgarshamsi, A ; Goharkhah, M ; Sharif University of Technology
    Sharif University of Technology  2013
    Abstract
    An analytical study using Variational Iteration Method (VIM) is carried out in order to investigate the vibrations of electro-statically actuated double-clamped and simply-supported microbeams. Effects of applied voltage and residual axial load on the nonlinear natural frequency and deflection of the microbeams are studied. It shows that pre-compression in microbeams increases the amplitude of deflections for a specific applied voltage. Also, an increase in pre-tension motivates the microbeam to show more nonlinear behavior in an applied voltage. Predicted results are compared with the experimental data available in the literature and also with numerical results which shows a good agreement.... 

    Nonlinear vibration analysis of a micro beam exposed to an external flow

    , Article ASME 2011 International Mechanical Engineering Congress and Exposition, IMECE 2011 ; Volume 7, Issue PARTS A AND B , 2011 , Pages 643-646 ; 9780791854938 (ISBN) Mazaheri, H ; Hosseinzadeh, A ; Ahmadian, M. T ; Barari, A ; Sharif University of Technology
    2011
    Abstract
    In this paper, nonlinear vibration of a micro cantilever exposed to a constant velocity flow is studied. In order to obtain vibration frequency and time response of the micro beam the variational iteration method is used as a novel tool for solving nonlinear differential equations. Results of the analytical solution are compared with those obtained by Runge-Kutta method which shows very good agreement between them. Results confirm that frequency of vibration depends on the flow velocity. Also, the high sensitivity of the vibration frequency to the flow velocity means that it can be an effective indicator of velocity  

    Fast microwave medical imaging based on iterative smoothed adaptive thresholding

    , Article IEEE Antennas and Wireless Propagation Letters ; Volume 14 , 2015 , Pages 438-441 ; 15361225 (ISSN) Azghani, M ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
    Abstract
    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  

    L2-Regularized Iterative Weighted Algorithm for Inverse Scattering

    , Article IEEE Transactions on Antennas and Propagation ; Volume 64, Issue 6 , 2016 , Pages 2293-2300 ; 0018926X (ISSN) Azghani, M ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    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... 

    Sparse and low-rank recovery using adaptive thresholding

    , Article Digital Signal Processing: A Review Journal ; Volume 73 , 2018 , Pages 145-152 ; 10512004 (ISSN) Zarmehi, N ; Marvasti, F ; Sharif University of Technology
    Elsevier Inc  2018
    Abstract
    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  

    A fast iterative method for removing sparse noise from sparse signals

    , Article 7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019, 11 November 2019 through 14 November 2019 ; 2019 ; 9781728127231 (ISBN) Sadrizadeh, S ; Zarmehi, N ; Marvasti, F ; Gazor, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    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... 

    Simultaneous Block Iterative Method with Adaptive Thresholding for Cooperative Spectrum Sensing

    , Article IEEE Transactions on Vehicular Technology ; Volume 68, Issue 6 , 2019 , Pages 5598-5605 ; 00189545 (ISSN) Azghani, M ; Abtahi, A ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    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...