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Total 23 records

    Designing an Estimation of Distribution Algorithm Based on Data Mining Methods

    , M.Sc. Thesis Sharif University of Technology Akbari Azirani, Elham (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    Estimation of distribution algorithms (EDA) are optimization methods that search the solution space by building and sampling probabilistic models. The linkage tree genetic algorithm (LTGA), which can be considered an estimation of distribution algorithm, uses hierarchical clustering to build a hierarchical linkage model called the linkage tree, and gene-pool optimal mixing algorithm to generate new solutions. While the LTGA performs very well on problems with separable sub-problems, its performance deteriorates on ones with overlapping sub-problems. This thesis presents a comparison of the effect of different pre-constructed models in the LTGA's performance. Several important factors that... 

    Designing an Estimation of Distribution Algorithm based on Learning Automata

    , M.Sc. Thesis Sharif University of Technology Moradabadi, Behnaz (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    Evolutionary algorithms are a type of stochastic optimization techniques influenced by genetics and natural evolution. Once the set of candidate solutions has been selected, a new generation is sampled by using recombination (crossover) and mutation operators to the candidate solutions. Public, fixed, problem independent mutation and recombination operators frequently lead to missing building blocks, knowledge of the relationship between variables and result in converging to a local optimum. A method to prevent disruption of building blocks is using the estimation of distribution algorithms (EDAs). The experimental results show that EDAs is capable to identify correct linkage between the... 

    New half-pixel accuracy motion estimation algorithms for low bitrate video communications

    , Article Scientia Iranica ; Volume 15, Issue 6 , 2008 , Pages 507-516 ; 10263098 (ISSN) Mahdavi Nasab, H ; Kasaei, S ; Sharif University of Technology
    Sharif University of Technology  2008
    Abstract
    Fractional-pixel accuracy Motion Estimation (ME) has been shown to result in higher quality reconstructed image sequences in hybrid video coding systems. However, the higher quality is achieved by notably increased Motion Field (MF) bitrate and more complex computations. In this paper, new half-pixel block matching ME algorithms are proposed to improve the rate-distortion characteristics of low bitrate video communications. The proposed methods tend to decrease the required video bandwidth, while improving the motion compensation quality. The key idea is to put a deeper focus on the search origin of the ME process, based on center-bias characteristics of low bitrate video MFs. To employ the... 

    Spare parts management algorithm for wind farms using structural reliability model and production estimation

    , Article IET Renewable Power Generation ; Volume 10, Issue 7 , Volume 10, Issue 7 , 2016 , Pages 1041-1047 ; 17521416 (ISSN) Mani, S ; Oraee, A ; Oraee, H ; Sharif University of Technology
    Institution of Engineering and Technology 
    Abstract
    Doubly fed induction generators (DFIGs) are widely used in wind power systems; hence their reliability model is an important consideration for production assessment and economic analysis of wind energy conversion systems. However, to date mutual influences of reliability analysis, production estimations and economic assessments of wind farms have not been fully investigated. This study proposes a reliability model for DFIG wind turbines considering their subcomponent failure rates and downtimes. The proposed production estimation algorithm leads to an economic assessment for wind farms. A comprehensive spare parts management procedure is then presented in the study. As a case study,... 

    3-point RANSAC for fast vision based rotation estimation using GPU technology

    , Article IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems9 February 2017 ; 2017 , Pages 212-217 ; 9781467397087 (ISBN) Kamran, D ; Manzuri, M. T ; Marjovi, A ; Karimian, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2017
    Abstract
    In many sensor fusion algorithms, the vision based RANdom Sample Consensus (RANSAC) method is used for estimating motion parameters for autonomous robots. Usually such algorithms estimate both translation and rotation parameters together which makes them inefficient solutions for merely rotation estimation purposes. This paper presents a novel 3-point RANSAC algorithm for estimating only the rotation parameters between two camera frames which can be utilized as a high rate source of information for a camera-IMU sensor fusion system. The main advantage of our proposed approach is that it performs less computations and requires fewer iterations for achieving the best result. Despite many... 

    Modified joint channel-and-data estimation for one-bit massive MIMO

    , Article 53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021, 22 May 2021 through 28 May 2021 ; Volume 2021-May , 2021 ; 02714310 (ISSN); 9781728192017 (ISBN) Bahari, M ; Rasoulinezhad, Ramin ; Amiri, M ; Gilani, F ; Saadatnejad, S ; Nezamalhosseini, A. R ; Shabany, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    Abstract
    Centralized and cloud computing-based network architectures are the promising tracks of future communication systems where a large scale compute power can be virtualized for various algorithms. These architectures rely on high-performance communication links between the base stations and the central computing systems. On the other hand, massive Multiple-Input Multiple-Output (MIMO) technology is a promising solution for base stations toward higher spectral efficiency. To reduce system complexity and energy consumption, 1-bit analog-to-digital converters (ADCs) are leveraged with the cost of lowering the signal quality. To recover the lost information, more sophisticated algorithms, like... 

    An iterative dictionary learning-based algorithm for DOA estimation

    , Article IEEE Communications Letters ; Volume 20, Issue 9 , 2016 , Pages 1784-1787 ; 10897798 (ISSN) Zamani, H ; Zayyani, H ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness... 

    Reduction of multi-path effect based on correlation decomposition in a DOA estimation system

    , Article Signal Processing and Intelligent Systems Conference, 16 December 2015 through 17 December 2015 ; 2015 , Pages 10-14 ; 9781509001392 (ISBN) Karimi, P ; Farzaneh, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    The multi-path phenomenon is one of the main causes of error in Direction Of Arrival Estimation systems which are located in a complex environment. The received signal in this environment consists of Line Of Sight (LOS) and multi-path components which are delayed versions of the LOS signal with the amplitude and the phase depending on the path length. In order to eliminate the multi-path signal, it is necessary to estimate the amplitude, the phase, and the delay of the signal. To this end, a method based on correlation which has been already used to estimate amplitudes and delays of Line Of Sight and multi-path signals in GPS systems, is implemented. After this estimation process, a phase... 

    Autonomous temperature-based orbit estimation

    , Article Aerospace Science and Technology ; Volume 86 , 2019 , Pages 671-682 ; 12709638 (ISSN) Nasihati Gourabi, F ; Kiani, M ; Pourtakdoust, H ; Sharif University of Technology
    Elsevier Masson SAS  2019
    Abstract
    Orbit estimation (OE) is a required significant task in almost all space missions. Accordingly, a wide variety of sensors and estimation algorithms have been developed within the last few decades to this aim. However, the current study proposes a novel autonomous OE method that is purely based on temperature data of six orthogonal surfaces of a three-axis stabilized satellite as it orbits around the Earth. While the utility of satellite surface temperature data has been recently investigated for satellite attitude estimation (AE) assuming its navigational information, the present paper is focused on OE via only temperature data that has not been attended to in the related literature. To this... 

    A distributed density estimation algorithm and its application to naive Bayes classification

    , Article Applied Soft Computing ; Volume 98 , 2021 ; 15684946 (ISSN) Khajenezhad, A ; Bashiri, M. A ; Beigy, H ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    We consider the problem of learning a density function from observations of an unknown underlying model in a distributed setting, where the observations are partitioned into different sites. Applying commonly used density estimation methods such as Gaussian Mixture Model (GMM) or Kernel Density Estimation (KDE) to distributed data leads to an extensive amount of communication. A familiar approach to address this issue is to sample a small subset of data and collect them into a central node to run the density estimation algorithms on them. In this paper, we follow an alternative to the sub-sampling approach by proposing the nested Log-Poly model. This model provides an accurate density... 

    Decoupled scalar approach for aircraft angular motion estimation using a gyro-free inertial measurement unit

    , Article Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME ; Volume 141, Issue 12 , 2019 ; 00220434 (ISSN) Dehghan Manshadi, A ; Saghafi, F ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2019
    Abstract
    In-flight aircraft angular motion estimation based on an all-accelerometers inertial measurement unit (IMU) is investigated in this study. The relative acceleration equation as the representative of a rigid-body kinematics is manipulated to present the state and measurement equations of the aircraft dynamics. A decoupled scalar form (DSF) of the system equations, as a free-singularity problem, is derived. Mathematical modeling and simulation of an aircraft dynamics, equipped with an all-accelerometers IMU, are employed to prepare measurement data. Taking into account the modeling of accelerometer error, the measurement data have been simulated as a real condition. Three extended Kalman... 

    On-line fault detection and isolation (FDI) for the exhaust path of a turbocharged SI engine

    , Article ASME 2013 Dynamic Systems and Control Conference, DSCC 2013 ; Vol. 1 , 2013 ; ISBN: 9780791856123 Salehi, R ; Shahbakhti M ; Alasty, A ; Vossoughi, G ; Sharif University of Technology
    Abstract
    Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold's input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically... 

    A new approach to estimate parameters of a lumped kinetic model for hydroconversion of heavy residue

    , Article Fuel ; Vol. 134, issue , 2014 , pp. 343-353 Asaee, S. D. S ; Vafajoo, L ; Khorasheh, F ; Sharif University of Technology
    Abstract
    The effect of complexity level of a lumped kinetic model for heavy residue hydroconversion on estimated values of kinetic parameters was investigated in this work by imposing constraints for the parameter estimation algorithm of a complex six-lump kinetic model and deriving a simpler modified model from the complex model. Kinetic analysis was performed using available experimental data reported in the literature from a study on hydrocracking of Chinese Gudao vacuum residue in a bench-scale reactor using ammonium phosphomolybdate (APM) as a dispersed catalyst. The kinetic models also included coke formation reactions that had previously been ignored by most investigators due to the rather... 

    A bayesian framework for sparse representation-based 3-d human pose estimation

    , Article IEEE Signal Processing Letters ; Vol. 21, issue. 3 , 2014 , pp. 297-300 ; ISSN: 10709908 Babagholami-Mohamadabadi, B ; Jourabloo, A ; Zarghami, A ; Kasaei, S ; Sharif University of Technology
    Abstract
    A Bayesian framework for 3-D human pose estimation from monocular images based on sparse representation (SR) is introduced. Our probabilistic approach aims at simultaneously learning two overcomplete dictionaries (one for the visual input space and the other for the pose space) with a shared sparse representation. Existing SR-based pose estimation approaches only offer a point estimation of the dictionary and the sparse codes. Therefore, they might be unreliable when the number of training examples is small. Our Bayesian framework estimates a posterior distribution for the sparse codes and the dictionaries from labeled training data. Hence, it is robust to overfitting on small-size training... 

    A unified approach for detection of induced epileptic seizures in rats using ECoG signals

    , Article Epilepsy and Behavior ; Volume 27, Issue 2 , 2013 , Pages 355-364 ; 15255050 (ISSN) Niknazar, M ; Mousavi, S. R ; Motaghi, S ; Dehghani, A ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Noorbakhsh, S. M ; Sharif University of Technology
    2013
    Abstract
    Objective: Epileptic seizure detection is a key step for epilepsy assessment. In this work, using the pentylenetetrazole (PTZ) model, seizures were induced in rats, and ECoG signals in interictal, preictal, ictal, and postictal periods were recorded. The recorded ECoG signals were then analyzed to detect epileptic seizures in the epileptic rats. Methods: Two different approaches were considered in this work: thresholding and classification. In the thresholding approach, a feature is calculated in consecutive windows, and the resulted index is tracked over time and compared with a threshold. The moment the index crosses the threshold is considered as the moment of seizure onset. In the... 

    On-line fault detection and isolation (FDI) for the exhaust path of a turbocharged SI engine

    , Article ASME 2013 Dynamic Systems and Control Conference, DSCC 2013 ; Volume 1 , 2013 ; 9780791856123 (ISBN) Salehi, R ; Shahbakhti, M ; Alasty, A ; Vossoughi, G ; Sharif University of Technology
    2013
    Abstract
    Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold's input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically... 

    A novel heuristic filter based on ant colony optimization for non-linear systems state estimation

    , Article Communications in Computer and Information Science, 27 October 2012 through 28 October 2012 ; Volume 316 CCIS , October , 2012 , Pages 20-29 ; 18650929 (ISSN) ; 9783642342882 (ISBN) Nobahari, H ; Sharifi, A ; Sharif University of Technology
    2012
    Abstract
    A new heuristic filter, called Continuous Ant Colony Filter, is proposed for non-linear systems state estimation. The new filter formulates the states estimation problem as a stochastic dynamic optimization problem and utilizes a colony of ants to find and track the best estimation. The ants search the state space dynamically in a similar scheme to the optimization algorithm, known as Continuous Ant Colony System. The performance of the new filter is evaluated for a nonlinear benchmark and the results are compared with those of Extended Kalman Filter and Particle Filter, showing improvements in terms of estimation accuracy  

    Low-rank matrix approximation using point-wise operators

    , Article IEEE Transactions on Information Theory ; Volume 58, Issue 1 , September , 2012 , Pages 302-310 ; 00189448 (ISSN) Amini, A ; Karbasi, A ; Marvasti, F ; Sharif University of Technology
    Abstract
    The problem of extracting low-dimensional structure from high-dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace, then simple algorithms using linear projections can find the subspace and consequently estimate its dimensionality. However, if the data lies on a low-dimensional but nonlinear space (e.g., manifolds), then its structure may be highly nonlinear and, hence, linear methods are doomed to fail. In this paper, we introduce a new technique for dimensionality reduction based on point-wise operators. More precisely, let $ {bf A} n... 

    MIMO radar waveform design in the presence of clutter

    , Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 47, Issue 2 , 2011 , Pages 770-781 ; 00189251 (ISSN) Naghibi, T ; Behnia, F ; Sharif University of Technology
    Abstract
    Waveform design for target identification and classification in multiple-input multiple-output (MIMO) radar systems has been studied in several recent works. In previous works, optimal signals for an estimation algorithm are found assuming that only signal- independent noise exists. This work extends previous research by studying the case where clutter is also present. We develop a procedure to design the optimal waveform which minimizes estimation error at the output of the minimum mean squared error (MMSE) estimators in two scenarios. In the first one different transmit antennas see uncorrelated aspects of the target, and we consider the correlated target aspects in the second one.... 

    A novel BEM- based channel estimation algorithm for time variant uplink OFDMA system

    , Article International Conference on Advanced Communication Technology, ICACT, 7 February 2010 through 10 February 2010 ; Volume 2 , Feb , 2010 , Pages 1289-1293 ; 17389445 (ISSN) ; 9788955191455 (ISBN) Ganji, F ; Tabatabavakili, V ; Samsami Khodadad, F ; Hosseinnezhad, M ; Safaei, A ; Sharif University of Technology
    2010
    Abstract
    IN this paper the effect of different channel estimation approaches in OFDMA uplink system which are based on Basis Expansion Model (BEM) and widely used to consider time varying channels are discussed. It has been shown in previous works that modeling error will be reduced by applying oversampled BEM with cost of increasing sensitivity to noise. This problem will be solved by combining oversampled BEM and MMSE channel estimator with cost of increasing computational complexity. In this paper a novel channel estimation approach is represented in which by combining oversampled BEM and low rank MMSE in frequency domain, almost the same performance as the full rank MMSE has been achieved while...