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Iranian Conference of Biomedical Engineering (ICBME)

作者： Mona Farokhzadi Hamid Soltanian-Zadeh Gholam-Ali Hossein-Zadeh Control and Intelligent Processing Center of Excellence (CIPCE) University of Tehran Tehran Iran

EEG source reconstruction is a challenging problem due to its ill-posed nature. In this research, we propose a multi-resolution version of the Multiple Sparse Prior (MSP) algorithm, such that the EEG inverse problem is solved in the low resolution space and the active regions are determined approximately then the source reconstruction is done in high resolution from the obtained source space. An advantage of this method is reducing the source space. Also, by locating the prior information in the active regions, the performance of the classic MSP algorithm improves and the higher model evidence is achieved because of importing the prior knowledge in to the problem. We use simulation to compare our proposed method with the classic MSP. We use the following performance measures to compare the methods: free energy, explained variance, relative root mean square error, and the spatial distance error. Our method outperforms the classic MSP in extracting the brain sources time series and their spatial maps.

关键词： Biomedical engineering 1/f noise Conferences

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Formulation and Numerical Solution for Fractional Order Time Optimal control Problem Using Pontryagin's Minimum Principle

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IFAC-PapersOnLine 2017年第1期50卷 9224-9229页

作者： Tabatabaei S.S. Yazdanpanah M.J. Tavazoei M.S. Electrical Engineering Department Amirkabair University of Technology (Tehran Polytechnic) Tehran Iran Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

The main purpose of this paper is to use variational calculus and Pontryagin's minimum principle to propose a solution scheme for time optimal control problem stated on the fractional systems defined in the sense of Caputo. After deriving the necessary optimality conditions, a novel numerical solution is used to solve the problem. Afterwards, a simple case study shows the effectiveness of the proposed method. © 2017

关键词： Non-integer Order Calculus Pontryagin's Minimum Principle Time Optimal control Variational Calculus

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Perturbed Tumor Immunotherapy Domain of Attraction Estimation via the Arc-Length Function

Perturbed Tumor Immunotherapy Domain of Attraction Estimatio...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Mojtaba Zarei Kimia Javadi Ahmad Kalhor Cyber-Physical Systems Lab (CPSL) Departments of Electrical and Computer Engineering Duke University NC USA Faculty of Computer and Electrical Engineering K.N.Toosi University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781538679531;9781538679524

This paper aims at the estimation of the Domain of Attraction (DoA) of the free tumor equilibrium point of perturbed tumor immunotherapy model via the Arc-Length Function (ALF). The ALFs are categorized among the maximal Lyapunov functions which are able to provide a more accurate estimation of the DoA in comparison to their other counterparts such as Rational Lyapunov Functions (RLFs), Sum Of Square (SOS) polynomial Lyapunov functions, and Optimal Quadratic Lyapunov Functions (OQLFs). There is no analytical method to construct the ALFs, however, some numerical methods have been proposed in the literature. Based on the existing method, one can approximate the ALF with a certain degree of a polynomial function. That the system under study has a polynomial structure was the main basis of the previously proposed method to estimate the DoA via the ALFs. However, the intended model in this paper describing the tumor-immune system competition dynamics contains non-polynomial terms. To cope with the aforementioned problem, the Taylor expansion of the non-polynomial terms are considered and by solving an optimization problem, one can calculate the corresponding lower boundary of the level set with the approximated ALF as an estimation of the DoA. In order to represent the performance of the employed method, the obtained result is compared with the reported result in the literature.

关键词： Tumors Direction-of-arrival estimation Lyapunov methods Estimation Immune system Mathematical model Cancer

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Equilibratability of control Systems

Equilibratability of Control Systems

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Iranian Conference on Electrical Engineering

作者： Ehsan Ghezelbash Mohammad Javad Yazdanpanah Abolfazl Yaghmaei School of ECE University of Tehran Tehran I. R. Iran Control & Intelligent Processing Center of Excellence University of Tehran Tehran I. R. Iran

In this paper, the problem of moving the equilibrium point of a control system to a desired point or desired space is considered. At the first stage of problem definition, the concept of equilibratability is introduced for the general class of nonlinear systems. Then, necessary and sufficient conditions for equilibratability of linear lime-invariant (LTI) systems are investigated for continuous and discrete time scenarios. Next, the problem of input selection based on equilibratability is proposed and investigated. When the input matrix is fixed and the system is not equilibratable at the desired point, an optimization problem is presented to select the nearest equilibratable point. Furthermore, when - instead of equilibrium point - an equilibrium space is sought, two supplementary optimization problems are put forward.

关键词： Equilibratability Input selection Sparse solution Zero optimization Equilibrium point modification

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Author Correction: Frontotemporal coordination predicts working memory performance and its local neural signatures

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Nature communications 2021年第1期12卷 3811页

作者： Ehsan Rezayat Mohammad-Reza A Dehaqani Kelsey Clark Zahra Bahmani Tirin Moore Behrad Noudoost School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran. School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran. dehaqani@ut.ac.ir. Cognitive Systems Laboratory Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran. dehaqani@ut.ac.ir. Department of Ophthalmology and Visual Sciences University of Utah Salt Lake City UT USA. Department of Biomedical Engineering Tarbiat Modares University Tehran Iran. Department of Neurobiology Stanford University Stanford CA USA. Howard Hughes Medical Institute Stanford University Stanford CA USA. Department of Ophthalmology and Visual Sciences University of Utah Salt Lake City UT USA. behrad.noudoost@utah.edu.

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A robust adaptive sliding mode controller for robot manipulators

A robust adaptive sliding mode controller for robot manipula...

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Artificial Intelligence and Robotics (IRANOPEN)

作者： Shaghayegh Gorji Mohammad Javad Yazdanpanah Department of Electrical Biomedical and Mechatronics Islamic Azad University Qazvin Iran Control and Intelligent Processing Center of Excellence University of Tehran Tehran I. R. Iran

ISBN: (纸本)9781538628638

In this paper, a novel adaptive sliding mode control for rigid robot manipulators is proposed. In the considered system, since there may exist explicit unknown system parameters and also perturbations, a lyapunov based approach is presented to increase system robustness, even in presence of arbitrarily large (but not infinite) discontinuous perturbations. The design contains two different phases of adaptation. The first one is related to the robot parameters and the other is accounted for perturbation estimating. A continuous controller is presented from the first step of design procedure. We try to prove the stability in the sense of lyapunov and derive adaptive laws and uniform ultimate boundedness in the worst condition. Simulation results for two degrees of freedom rigid robot manipulator effectively demonstrate the capability of mentioned approach.

关键词： Uncertainty Robustness Manipulators Upper bound Stability analysis Simulation

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On stabilization and output tracking of a class of nonlinear systems via new backstepping-like methods

On stabilization and output tracking of a class of nonlinear...

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IEEE Annual Conference on Decision and control

作者： M. Bahraini M.J. Yazdanpanah School of Electrical and Computer Engineering’ University of Tehran Tehran I. R. Iran Control & Intelligent Processing Center of Excellence University of Tehran Tehran I. R. Iran

In this article, controller design for a class of nonlinear systems is considered. The strict feedback form is a special case of this class and the proposed method is an extension to the backstepping method. In general form, the proposed method suggests a dynamical controller which has one state less than the system. However, the controller order is not fixed and it may be less than the general form. In a special case, the proposed controller reduces into a static function which is the original backstepping method. The proposed method can be used for stabilization and output tracking for this class which may be quite complicated or even impossible with regular methods. The proposed control strategy is based on the stability of the augmented states. In case that the assumption does not hold, another strategy is suggested to be used for stabilization.

关键词： Backstepping Robustness Mechanical systems Couplings Nonlinear systems

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A chain observer for nonlinear long constant delay systems: A matrix inequality approach

A chain observer for nonlinear long constant delay systems: ...

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作者： Vafaei, Alaleh Yazdanpanah, Mohammad Javad Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran PO Box 14395/515 Tehran Iran

This paper proposes a new state observer for nonlinear systems with non negligible and different time delays in the state, output and input and Lipschitz nonlinearity. The proposed observer is composed of a chain of observers with similar algorithm. Each of them estimates the states in different time instants, while the last observer estimates the state in the present time. Conditions for stability of the observer are translated into linear matrix inequalities (LMIs) which facilitates the design of observer gains. Simulation results demonstrate effectiveness of this observer. © 2015 Elsevier Ltd. All rights reserved.

关键词： Nonlinear systems

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Incremental learning of high-level concepts by imitation

arXiv

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arXiv 2017年

作者： Alibeigi, Mina Ahmadabadi, Majid Nili Araabi, Babak Nadjar Cognitive Systems Lab School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Cognitive Systems Lab. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Tehran Iran

Nowadays, robots become a companion in everyday life. To be well-accepted by humans, robots should efficiently understand meanings of their partners’ motions and body language, and respond accordingly. Learning concepts by imitation brings them this ability in a user-friendly way. This paper presents a fast and robust model for Incremental Learning of Concepts by Imitation (ILoCI). In ILoCI, observed multimodal spatio-temporal demonstrations are incrementally abstracted and generalized based on both their perceptual and functional similarities during the imitation. In this method, perceptually similar demonstrations are abstracted by a dynamic model of mirror neuron system. An incremental method is proposed to learn their functional similarities through a limited number of interactions with the teacher. Learning all concepts together by the proposed memory rehearsal enables robot to utilize the common structural relations among concepts which not only expedites the learning process especially at the initial stages, but also improves the generalization ability and the robustness against discrepancies between observed demonstrations. Performance of ILoCI is assessed using standard LASA handwriting benchmark data set. The results show efficiency of ILoCI in concept acquisition, recognition and generation in addition to its robustness against variability in demonstrations. Copyright © 2017, The Authors. All rights reserved.

关键词： Abstracting

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Non-linear feature extraction from HRV signal for mortality prediction of ICU cardiovascular patient

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Journal of Medical Engineering and Technology 2016年第3期40卷 87-98页

作者： Moridani, Mohammad Karimi Setarehdan, Seyed Kamaledin Motie Nasrabadi, Ali Hajinasrollah, Esmaeil Department of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Centre of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Departments of Biomedical Engineering Shahed University Tehran Iran Loghman Medical Center Shahid Beheshti University of Medical Sciences Tehran Iran

Intensive care unit (ICU) patients are at risk of in-ICU morbidities and mortality, making specific systems for identifying at-risk patients a necessity for improving clinical care. This study presents a new method for predicting in-hospital mortality using heart rate variability (HRV) collected from the times of a patients ICU stay. In this paper, a HRV time series processing based method is proposed for mortality prediction of ICU cardiovascular patients. HRV signals were obtained measuring R-R time intervals. A novel method, named return map, is then developed that reveals useful information from the HRV time series. This study also proposed several features that can be extracted from the return map, including the angle between two vectors, the area of triangles formed by successive points, shortest distance to 45° line and their various combinations. Finally, a thresholding technique is proposed to extract the risk period and to predict mortality. The data used to evaluate the proposed algorithm obtained from 80 cardiovascular ICU patients, from the first 48 h of the first ICU stay of 40 males and 40 females. This study showed that the angle feature has on average a sensitivity of 87.5% (with 12 false alarms), the area feature has on average a sensitivity of 89.58% (with 10 false alarms), the shortest distance feature has on average a sensitivity of 85.42% (with 14 false alarms) and, finally, the combined feature has on average a sensitivity of 92.71% (with seven false alarms). The results showed that the last half an hour before the patients death is very informative for diagnosing the patients condition and to save his/her life. These results confirm that it is possible to predict mortality based on the features introduced in this paper, relying on the variations of the HRV dynamic characteristics. © 2016 Taylor & Francis.

关键词： Forecasting

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