Search for: bayesian-estimations
Online Health Monitoring of Nonlinear Hysteretic Structures Using System Identification Techniques and Signal Processing Tools, Ph.D. Dissertation Sharif University of Technology ; Bakhshi, Ali
Adverse social and economic effects of earthquakes have necessitated the emergence and development of efficient methods to assess and monitor the health status of structures. Many of the structural health monitoring algorithms are based on linear models that are not able to provide sufficient dynamic information. Nonlinear models require monitoring of a larger number of structural parameters and provide a much closer to reality model of the structure. Therefore, the use of nonlinear models in the identification process provides more useful information about the safety and serviceability of post-earthquake structures. Also, most of the existing methods are not applicable for online health...
M.Sc. Thesis Sharif University of Technology ; Nobakhti, Amin ; Babazadeh, Maryam
Television, radio, newspaper, magazines, and billboards are among the major channels that traditionally place ads, however, the advancement of the Internet enables users to seek information online. In display and mobile advertising, the most significant technical development in recent years is the growth of Real-Time Bidding (RTB), which facilitates a real-time auction for a display opportunity. Real-time means the auction is per impression and the process usually occurs less than 300 milliseconds before the ad is placed. RTB has fundamentally changed the landscape of the digital media market by scaling the buying process across a large number of available inventories among publishers in an...
M.Sc. Thesis Sharif University of Technology ; Nasiri Kenari, Masoumeh ; Aminzadeh Gohari, Amin
In recent years, molecular communications have received considerable attentions for communication between nano-machines. In this communication scheme, which uses molecules as information carriers, nano transmitter and receiver are in distance apart of nano meter to meter and information is encoded into type, concentration or releasing time of molecules. Since nano transmitter and receiver can do very simple operations, such as adding, sensing, and etc., for more complicated operations, a network of nano transceivers is required. In this thesis, a small scale imaging of an abnormality in the environment is investigated. To this end, a network of sensors is assumed to be placed in the...
M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza
Error concealment is one of the effective ways to alleviate the effect of packet loss in video communication over error-prone environments. In order to estimate lost macro-blocks, we have employed Bayesian estimation as an efficient and robust framework. Gaussian process regression has been used as the modeling approach through this framework. Considering luminance component as Gaussian process,a minimum mean squared error estimation of the lost macro-block is obtained. This estimator, as a function of the existing data, is only determined by the covariance matrix defined over them. Therefore,the main step in Gaussian process regression, is construction of the convenient covariance matrix...
Sequential Bayesian estimation of state and input in dynamical systems using output-only measurements, Article Mechanical Systems and Signal Processing ; Volume 131 , 2019 , Pages 659-688 ; 08883270 (ISSN) ; Papadimitriou, C ; Teymouri, D ; Katafygiotis, L. S ; Sharif University of Technology
Academic Press 2019
The problem of joint estimation of the state and input in linear time-invariant dynamical systems is revisited proposing novel sequential Bayesian formulations. An appealing feature of the proposed method is the promise it delivers for updating the covariance matrices of the process and measurement noise in a real-time fashion using asymptotic approximations. The proposed method avoids the direct transmission of the input into predictions of the state using a zero-mean Gaussian distribution for the input. This prior distribution aims to eliminate low-frequency drifts from estimations of the state and input. Moreover, the method is outlined in a computational algorithm offering real-time...
Performance evaluation of the Bayesian and classical value at risk models with circuit breakers set up, Article International Journal of Computational Economics and Econometrics ; Volume 10, Issue 3 , 10 June , 2020 , Pages 222-241 ; Online ISSN: 1757-1189 ; Heidari, H ; Sharif University of Technology
Inderscience Publishers 2020
Circuit breakers, like price limits and trading suspensions, are used to reduce price volatility in security markets. When returns hit price limits or missed, observed returns deviate from equilibrium returns. This creates a challenge for predicting stock returns and modelling value at risk (VaR). In Tehran Stock Exchange (TSE), the circuit breakers are applied to control for the excess price volatilities. This paper intend to address which models and what methodology should be applied by risk analysts to calculate the VaR when the returns are unobservable. To this end, we extend Wei’s (2002) model, in the framework of Bayesian Censored and Missing-GARCH approach, to estimate VaR for a share...
Article Engineering Structures ; Volume 239 , 2021 ; 01410296 (ISSN) ; Eftekhar Azam, S ; Mofid, M ; Sharif University of Technology
Elsevier Ltd 2021
This study introduces a novel Bayesian framework for online and real-time vibration control of beam type structures, which represent a comprehensive control system associated with input-state algorithms. Control design systems typically require knowledge of system states, which in structures are displacements and velocities at some degrees of freedom. Currently, full-field measurements of displacements and velocities in large structural systems are not feasible. Also, properties of the moving inertial loads as key parameters in control designs are assumed known; however, in practice, measuring their characteristics is a challenging issue. As a remedy, an observer is required to estimate...
Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 51, Issue 1 , April , 2015 , Pages 739-743 ; 00189251 (ISSN) ; Saghafi, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2015
An algorithm, by cooperation of multiple flying vehicles, is developed to localize a moving target in the presence of measurement noise and mis-modeling. It works based on jointly sharing information and data fusion by using a recursive Bayesian estimator and a searching guidance law to direct each flying vehicle to a position where the probability of target detection is maximum. To evaluate this algorithm, a high fidelity simulation program with six degrees of freedom dynamics is also developed
Article ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 22 May 2011 through 27 May 2011 ; May , 2011 , Pages 953-956 ; 15206149 (ISSN) ; 9781457705397 (ISBN) ; Bayati, A ; Rabiee, H. R ; Rohban, M. H ; Sharif University of Technology
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem of estimating the lost motion vectors is modelled as a kernel construction problem in a Bayesian framework. First, to describe the similarity between the neighboring motion vectors, a kernel function is defined. Then the parameters of the kernel function is estimated as the coefficients of a linear Bayesian estimator. The experimental results verify the superiority of the proposed algorithm over the conventional and state of the art motion vector concealment methods. Moreover, noticeable improvements on both...
A heuristic threshold policy for fault detection and diagnosis in multivariate statistical quality control environments, Article International Journal of Advanced Manufacturing Technology ; Volume 67, Issue 5-8 , July , 2013 , Pages 1231-1243 ; 02683768 (ISSN) ; Niaki, S. T. A ; Sharif University of Technology
In this paper, a heuristic threshold policy is developed to detect and classify the states of a multivariate quality control system. In this approach, a probability measure called belief is first assigned to the quality characteristics and then the posterior belief of out-of-control characteristics is updated by taking new observations and using a Bayesian rule. If the posterior belief is more than a decision threshold, called minimum acceptable belief determined using a heuristic threshold policy, then the corresponding quality characteristic is classified out-of-control. Besides using a different approach, the main difference between the current research and previous works is that the...