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Sensitivity function of LTI fractional order dynamic systems with respect to the orders

Sensitivity function of LTI fractional order dynamic systems...

引用

American control Conference (ACC)

作者： Yan Li Dingyü Dingyü Xue YangQuan Chen Center of Self-Organizing & Intelligent Systems CSOIS Electrical an Computer Engineering Department Utah State University Logan UT USA School of Control Science and Engineering Shandong University Jinan Shandong China Institute of Robotics and Artificial Intelligent School of Information Science and Engineering Northeastern University Shenyang China

Many real natural or man-made dynamic systems can be better characterized using a fractional order dynamic model. Since in such a case the order assumes a non-integer value, it is of interest to consider the effect of small perturbation around the nominal value. It is of practical importance to analyze the influence of the order variations on the system behavior. This paper establishes an analytical method for the analysis of the sensitivity function of LTI fractional order dynamic systems with respect to the orders. The continuous dependent condition of the orders of fractional Green's function is derived, which is proved as a necessary and sufficient condition. The singularity of fractional Green's functions is discussed. Several examples are included for illustration.

关键词： Green's function methods Lyapunov method Intelligent robots Sufficient conditions Artificial intelligence Transfer functions Fractional calculus Integral equations Partial differential equations H infinity control

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A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation

A statistical shape model using 2D-principal component analy...

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International Conference on Software engineering and Data Mining (SEDM)

作者： Tomoko Tateyama Taishi Tanaka Shinya Kohara Amir Hossein Foruzan Akira Furukawa Yen-Wei Chen Intelligent Image Processing Laboratory College of Information Science and Engineering Ritsumeikan University Shiga Japan Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Radiology Shiga University of Medical Science Shiga Japan

ISBN: (纸本)9781424473243;9788988678220;9788988678213

Since the medical training samples are very limited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good generalization even using fewer samples.

关键词： Biomedical imaging Shape control Biomedical engineering Principal component analysis Liver Information analysis Educational institutions Azimuth Covariance matrix Image analysis

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A new scheme for evaluation of air-trapping in CT images

A new scheme for evaluation of air-trapping in CT images

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Iranian Machine Vision and Image Processing (MVIP)

作者： M. Parsa Hosseini Hamid Soltanian-Zadeh Shahram Akhlaghpoor Alireza Behrad Department of Electrical Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Department of Radiology Sina Hospital Tehran University of Medical Sciences Tehran Iran Department of Electrical Engineering Shahed University Tehran Iran

Air trapping is an abnormal retention of air that occurs after expiration state in the lungs, observed in all types of bronchiolar and obstructive lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and bronchiolitis obliterans syndrome. Air trapping is often incidentally diagnosed on computed tomography (CT) scanning but this method needs doctors so it is subjective and depends on their experience. In this paper, we present a novel method for evaluation of air trapping in the lungs for detection of COPD in CT images. The proposed method finds volumetric variations of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared and the volumetric variations are used to classify the subjects. In the evaluated cases, the proposed method is able to estimate air trapping in the lungs from CT images without human intervention. This method may assist radiologists to measure and evaluate air trapping for detection of COPD as a computer aided diagnosis (CAD) system.

关键词： Lungs Computed tomography Charge carrier processes Diseases Image segmentation Biomedical imaging

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： Mahdi Ramezani Amin Heidari Emad Fatemizadeh Hamid Soltanian-Zadeh Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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Multiple-atlas-based automatic sementation of hippocampus for lateralization in temporal lobe epilepsy

Multiple-atlas-based automatic sementation of hippocampus fo...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi-Asl Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Image Analysis Laboratory Department of Diagnostic Radiology Henry Ford Health System Detroit MI USA School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259

We introduce a 3D segmentation framework which uses principal shapes. The probabilistic energy function of the method is defined based on intensity, tissue type, and location information of the structures using a multiple atlas method. For intensity information, nonparametric probability density function is used which considers intensity relation of different structures. To find a local minimum of the energy function, a two-step optimization strategy is used. In the first step, shape parameters are optimized based on the analytic derivatives of the energy function. In the second step, shapes of the structures are fine-tuned using a level set method. The proposed method is shown to be superior to some popular methods in the literature using a dataset of 64 patients with mesial temporal lobe epilepsy. In addition, the method can be used for lateralization with accuracy close to that of manual segmentation.

关键词： Hippocampus Temporal lobe Epilepsy Image segmentation Principal component analysis Shape control Probability density function Level set Skull Algorithm design and analysis

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Extended Kalman filtering of point process observation

Extended Kalman filtering of point process observation

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yousef Salimpour Hamid Soltanian-Zadeh Mohammad D. Abolhassani Neuroscience and Neuroengineering in School of Cognitive Sciences Institute of Studies in Fundamental Sciences IPM and Research Group for Brain and Cognitive Sciences School of Medicine Shahid Beheshti University Tehran Iran Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Tehran University of Medical Sciences Tehran Tehran IR

A temporal point process is a stochastic time series of binary events that occurs in continuous time. In computational neuroscience, the point process is used to model neuronal spiking activity; however, estimating the model parameters from spike train is a challenging problem. The state space point process filtering theory is a new technique for the estimation of the states and parameters. In order to use the stochastic filtering theory for the states of neuronal system with the Gaussian assumption, we apply the extended Kalman filter. In this regard, the extended Kalman filtering equations are derived for the point process observation. We illustrate the new filtering algorithm by estimating the effect of visual stimulus on the spiking activity of object selective neurons from the inferior temporal cortex of macaque monkey. Based on the goodness-offit assessment, the extended Kalman filter provides more accurate state estimate than the conventional methods.

关键词： Mathematical model Equations Kalman filters Neurons Computational modeling Estimation

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Speeding up top-down attention control learning by using full observation knowledge

Speeding up top-down attention control learning by using ful...

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2009 IEEE International Symposium on Computational Intelligence in robotics and Automation, CIRA 2009

作者： Noori, N. Nili Ahmadabadi, M. Mirian, M.S. Araabi, B.N. Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

We present a general mathematical description of the top-down attention control problem. Three important components are identified in the model: context extraction, attention focus and decision making. The context gives a coarse blurry representation of the whole input;the attention module models the focus of attention on a limited part of input, and the decision making component accounts the final decision of the agent for its motory actions. In order to achieve a faster convergence of attention learning in the online phase, an offline optimization step is performed in advance. To do so, we incorporate the knowledge of a full observer agent that has approximately learned the optimal decision making of the task. The simulation results show that by employing our algorithm, the learning speed is improved.

关键词： Decision making

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A novel routine test schedule for protective systems using an extended component-based reliability model

A novel routine test schedule for protective systems using a...

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6th International Conference on electrical and Electronics engineering, ELECO 2009

作者： Abbarin, A. Fotuhi-Firuzabad, M. Center of Excellence in Power System Control and Management Department of Electrical Engineering Sharif University of Technology Tehran Iran

ISBN: (纸本)9789944898188

This paper presents a novel approach for evaluating the reliability of protective systems taking into account its components reliability. In this paper, a previously proposed extended model is used for Directional Overcurrent scheme. In the extended model, the impacts of individual protective components are taken into account. An optimum routine test schedule is determined for each protective component as a separate unit. A comparison is made to show that the proposed approach has excellence over conventional routine test inspections. Impacts of factors such as circuit breaker inadvertent opening, required time for performing routine test inspections, human mistakes and self-checking and monitoring effectiveness is analyzed using the model. Redundancy in some parts of the protective system is examined. Permanent and transient faults on the protected zone, operation of backup protection and Common-Cause failures are also recognized in the model.

关键词： Redundancy

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Fuzzy controller for cooperative object pushing with variable line contact

Fuzzy controller for cooperative object pushing with variabl...

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International Conference on Mechatronics (ICM)

作者： Mahsa Aliakbar Golkar Sarah Taghavi Namin Hossein Aminaiee Control and Intelligent Processing Center of Excellence Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran

Designing an appropriate cooperation protocol in multi-robot systems such as multi-robot object manipulation systems is a challenging task. In this paper designing and implementing a cooperation protocol between two robots pushing an object toward an arbitrary goal configuration is investigated. The proposed method benefits from task decoupling which simplifies the cooperation protocol design. Each robot gets its proper action from a particular fuzzy inference system independently. The fuzzy controllers outputs are low-level robot commands by which the need to a robot path planning algorithm is eliminated. Simulation results show that robots could push the object to the goal configuration cooperatively. Experiments have been conducted to approve the proposed system.

关键词： Fuzzy control Robot kinematics Protocols Fuzzy systems Electric variables control control systems Multirobot systems Path planning Inference algorithms Mobile robots

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Simultaneously, speed and flux control of a induction motor, with brain emotional learning based intelligent controller (BELBIC)

Simultaneously, speed and flux control of a induction motor,...

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2009 IEEE International Electric Machines and Drives Conference, IEMDC '09

作者： Daryabeigi, E. Markadeh, Arab Lucas, C. Department of Electrical Engineering Islamic Azad university Young Researcher Club Esfahan Iran Faculty of engineering department Shahrekord University Shahrekord Iran Department of Iranian Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran

ISBN: (纸本)9781424442522

In this paper, a modern intelligent control based on computational model of mammalian limbic system and emotional processes (BELBIC) is presented for speed and flux control of induction motor simultaneously. In this work, a novel and simple model of induction motor drives control plant is achieved by using the intelligent control system, which controls motor speed and flux accurately, without needing to using any conventional controllers and also, quite independent of motor parameters. This generation of intelligent controllers that has high auto learning speed with simple structure shows excellent praxis for industrial scale utilization truly. © 2009 IEEE.

关键词： Induction motors

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