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Progressive sparse image sensing using Iterative Methods
, Article 2012 6th International Symposium on Telecommunications, IST 2012 ; 2012 , Pages 897-901 ; 9781467320733 (ISBN) ; 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...
Iterative least squares algorithm for inverse problem in MicroWave medical imaging
, Article European Signal Processing Conference, 28 August 2016 through 2 September 2016 ; Volume 2016-November , 2016 , Pages 341-344 ; 22195491 (ISSN) ; 9780992862657 (ISBN) ; Marvasti, F ; Sharif University of Technology
European Signal Processing Conference, EUSIPCO
2016
Abstract
The inverse problem in MicroWave Imaging (MWI) is an ill-posed one which can be solved with the aid of the sparsity prior of the solution. In this paper, an Iterative Least Squares Algorithm (ILSA) has been proposed as an inverse solver in MWI which seeks for the sparse vector satisfying the problem constraints. Minimizing a least squares cost function, we derive a relatively simple iterative algorithm which enforces the sparsity gradually with the aid of a reweighting operator. The simulation results confirm the superiority of the suggested method compared to the state-of-the-art schemes in the quality of the recovered breast tumors in the microwave images
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) ; Marvasti, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
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...
Efficient Iterative Sparse Recovery Techniques
, Ph.D. Dissertation Sharif University of Technology ; Marvasti, Farokh (Supervisor)
Abstract
In this thesis, we aim to explore the recovery of sparse signals from their compressive or random samples. At first, the Compressed Sensing (CS) recovery is considered and an iterative method with adaptive thresholding has been suggested which has superior performance compared to its counterparts in both reconstruction quality and simplicity. Then, random sampling, a special kind of compressive sensing, is investigated which is practically more efficient to be implemented than the compressive sampling scheme. A number of random sampling recovery techniques are offered based on sparsity which has very low computational complexity in a way that largedimensional signals can efficiently be...
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 ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
2014
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...
Towards optimization of toeplitz matrices for compressed sensing
, Article 2013 Iran Workshop on Communication and Information Theory ; May , 2013 , Page(s): 1 - 5 ; 9781467350235 (ISBN) ; Aghagolzadeh, A ; Marvasti, F ; Sharif University of Technology
2013
Abstract
ABSTRACT Compressed sensing is a new theory that samples a signal below the Nyquist rate. While Gaussian and Bernoulli random measurements perform quite well on the average, structured matrices such as Toeplitz are mostly used in practice due to their simplicity. However, the signal compression performance may not be acceptable. In this paper, we propose to optimize the Toeplitz matrices to improve its compression performance to recover sparse signals. We establish the optimization on minimizing the coherence of the measurement matrix by an intelligent optimization method called Particle Swarm Optimization. Our simulation results show that the optimized Toeplitz matrix outperforms the...
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) ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
2015
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
Microwave medical imaging based on sparsity and an iterative method with adaptive thresholding
, Article IEEE Transactions on Medical Imaging ; Volume 34, Issue 2 , September , 2015 , Pages 357-365 ; 02780062 (ISSN) ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
We propose a new image recovery method to improve the resolution in microwave imaging applications. Scattered field data obtained from a simplified breast model with closely located targets is used to formulate an electromagnetic inverse scattering problem, which is then solved using the Distorted Born Iterative Method (DBIM). At each iteration of the DBIM method, an underdetermined set of linear equations is solved using our proposed sparse recovery algorithm, IMATCS. Our results demonstrate the ability of the proposed method to recover small targets in cases where traditional DBIM approaches fail. Furthermore, in order to regularize the sparse recovery algorithm, we propose a novel...
Multihypothesis compressed video sensing technique
, Article IEEE Transactions on Circuits and Systems for Video Technology ; Volume 26, Issue 4 , 2016 , Pages 627-635 ; 10518215 (ISSN) ; Karimi, M ; Marvasti, F ; Sharif University of Technology
2016
Abstract
In this paper, we present a compressive sampling and multihypothesis (MH) reconstruction strategy for video sequences that has a rather simple encoder, while the decoding system is not that complex. We introduce a convex cost function that incorporates the MH technique with the sparsity constraint and the Tikhonov regularization. Consequently, we derive a new iterative algorithm based on these criteria. This algorithm surpasses its counterparts (Elasticnet and Tikhonov) in recovery performance. Besides, it is computationally much faster than Elasticnet and comparable with Tikhonov. Our extensive simulation results confirm these claims
Blind Iterative Non-linear Distortion Compensation Based on Thresholding
, Article IEEE Transactions on Circuits and Systems II: Express Briefs ; Volume PP, Issue 99 , 2016 ; 15497747 (ISSN) ; Ghorbani, A ; Marvasti, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
The sampling process in electrical devices includes non-linear distortion which needs to be compensated to boost up the system efficiency. In this paper, a blind method is suggested for non-linear distortion compensation. The core idea is to leverage the sparsity of the signal to cope with the ill-posedness of the distortion compensation task. The proposed scheme is an iterative method based on out of support energy minmization where the support information is not available. An adaptive thresholding operator is used to give a rough approximation of the support according to the estimated signal at each iteration. Various simulation scenarios have validated the capability of the suggested...
Blind iterative nonlinear distortion compensation based on thresholding
, Article IEEE Transactions on Circuits and Systems II: Express Briefs ; Volume 64, Issue 7 , Volume 64, Issue 7 , 2017 , Pages 852-856 ; 15497747 (ISSN) ; Ghorbani, A ; Marvasti, F ; Sharif University of Technology
2017
Abstract
The sampling process in electrical devices includes nonlinear distortion that needs to be compensated to boost up the system efficiency. In this brief, a blind method is suggested for nonlinear distortion compensation. The core idea is to leverage the sparsity of the signal to cope with the ill-posedness of the distortion compensation task. The proposed scheme is an iterative method based on out of support energy minimization, in which the support information is not available. An adaptive thresholding operator is used to give a rough approximation of the support according to the estimated signal at each iteration. Various simulation scenarios have validated the capability of the suggested...
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) ; 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...
Lumbopelvic Rhythm during Forward and Backward Sagittal Trunk Rotations; in vivo Measurements Using Inertial Sensors
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Direct in vivo measurements of spinal loads and muscle forces are invasive. Investigators have thus used musculoskeletal biomechanical models that require kinematic data including trunk and pelvis angular movements as their inputs. . Novel devices measure anglular movements using both inertial sensors (such as gyroscopes and accelerometers) and miniature magnetometers. Relative low cost, portability, and accuracy are among specific characteristics of inertial tracking devices. The main objective of the present study was set to measure spinal kinematics including the lumbopelvic rhythm as the ratio of total lumbar rotation over pelvic rotation during trunk sagittal movement which is essential...
Evaluation of 1991 NIOSH Lifting Equation in Controlling the Biomechanical Loads of the Human Spine
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
The 1991 NIOSH Lifting Equation (NLE) is widely used to assess risk of injury to the spine by providing estimates of the recommended weight limit (RWL) in hands. The present study uses two biomechanical models of the spine to verify whether the RWL generates L5-S1 loads within the limits (e.g., 3400 N for compression recommended by NIOSH and 1000 N for shear recommended in some studies).Severallifting activities are simulated here to evaluate the RWL by the NLE and the L5-S1 loads by the models. In lifting activities involving moderate to large forward trunk flexion, the estimated RWL generates L5-S1 spine loads exceeding the recommended limits. The NIOSH vertical multiplier is the likely...
Sagittal Range of Motion of the Thoracic Spine Using Inertial Tracking Device and Effect of Measurement Errors on Model Predictions
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Range of motion (ROM) of the thoracic spine has implications in patient discrimination for diagnostic purposes and in biomechanical models for predictions of spinal loads. Few previous studies have reported quite different thoracic ROMs. Total (T1-T12), lower (T5-T12) and upper (T1-T5) thoracic, lumbar (T12-S1), pelvis, and entire trunk (T1) ROMs were measured using an inertial tracking device as asymptomatic subjects flexed forward from their neutral upright position to full forward flexion. Correlations between body height and the ROMs were conducted. Effect of measurement errors of the trunk flexion (T1) on the model-predicted spinal loads was investigated. Mean of peak voluntary total...
A Detailed Finite Element Model of the Lumbar Spine under Muscle Forces
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Etiological studies proves the fact that Low Back Pain (LBP) is one of the most expensive and prevalent desease all over the world. This fact illustrates the reqiurment of the special effort in ordet to reducing the pain due to this problem. Finite element modeling of human spine is one the suitable methods to simulate the behavior of human spine in different loading conditions. These conditions could be different daily occupational tasks. There is two general viewpoint toward finite element modeling of human spine. The fisrt method focuses on the detailed geometry and mechanical properties of spine, while the other complexities such as detailed muscle forces are overlooked. The latter...
A Hyrid EMG-optimization Based Model of the Lumbar Spine to Estimate Muscle Forces in Different Tasks
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Low back pains (LBP) are prevalent and costly. One of the important factors causing LBP is excessive axial compression and shear forces that are applied on the intervertebral discs during different activities. Due to lack of direct in vivo measurement methods for estimating these loads, musculoskeletal biomechanical models have been emerged as indispensable tools under various activities. Different biomechanical models have been suggested to estimate muscle forces and spinal loads base on optimization, EMG and hybrid (EMG assisted optimization, EMGAO) methods. Although there have been a number of studies on the differences between various optimization and EMG-based methods, there has been no...
Effect of Iatrogenic Muscle Injuries on Spine Biomechanics During Posterior Lumbar Surgeries Using a Biomechanical Model for Design of Rehabilitation Exercises
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Posterior lumbar surgery is often associated with extensive injuries to back muscles. In this thesis, the effect of such iatrogenic injuries in some patients was examined. For this purpose, the CSA of back muscles in 6 patients were measured using MR scan. To examine any natural change in CSAs of healthy people or instrument errors, same measurement were carried out on 10 healthy volunteers. In addition, a detailed anatomical model of an intact human spine was developed. With the aim of experimental studies and intact model, the post-operative model of patients was also developed. These two models were used to quantizing the change in activity of back muscles during some symmetric, normal...
3D Measurements of the Thoracic and Lumbar Spine Range of Motions Using Inertial Sensors
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
Musculoskeletal abnormalities affect joints and change their range of motion (RoM). Correcting these abnormalities thoroughly depends on the information related to the normal spine movement. Therefore, spine motion analysis can be used as an important tool to distinguish between healthy and patient individuals as well as to determine the intensity of such diseases. Additionally, existing biomechanical models need kinematics data in order to analyze spinal forces. The present study hence aims to measure 3D range of motion of thoracic and lumbar spine using inertial sensors. Their small size, portability, low weight, and relatively low cost make inertial sensors as indispensable tools in...
A Novel Stability-based EMG-assisted Model of the Lumbar Spine to Estimate Trunk Muscle Forces and Spinal Loads in Various Static Activities
, M.Sc. Thesis Sharif University of Technology ; Arjmand, Navid (Supervisor)
Abstract
The spine like every other mechanical pillar, is exposed to buckling and loss of stability. While existing biomechanical models emphasize the pressure force on the disk as the main cause of injury, there is also a possibility of local buckling phenomenon in vertebral discs. Because of the prevalence and high cost of lower back pain, it is essential to evaluate the forces carried by disks and lumbar muscles during occupational activities more accurately. In this regard, hybrid EMG-assisted optimization (EMGAO) approaches are most common methods for estimation of spinal loads. These models, not only use EMG data to be physiologically creditable, but also satisfy equilibrium requirements at all...