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检索条件"机构=School of Electrical and Computer Engineering Intelligent Systems and Control Laboratory"

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Comparison of voxel-based morphometry (VBM) and tractography of diffusion tensor MRI (DT-MRI) in temporal lobe epilepsy

Comparison of voxel-based morphometry (VBM) and tractography...

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Iranian Conference on electrical engineering (ICEE)

作者： Maryam Afzali Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

ISBN: (纸本)9781424467600

Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain that harbor seizure focus is a critical step towards treatment of TLE patients. Diffusion tensor imaging (DTI) is a non-invasive method that we use in this work to determine damaged regions of white matter in the brain. To this end, we apply two methods, voxel based morphometry (VBM) and fiber tracking. We use these methods along with two anisotropy maps (EAR and FA) extracted from the DTI data. We use DTI data of 31 subjects (12 normal subjects and 19 TLE patients) for testing and evaluation studies. The VBM method shows that TLE is associated with reduction of both of FA and EAR values in several regions within the temporal lobes. The tractography method shows abnormal diffusion characteristics in three fiber bundles (fornix, uncinate fasciculus, and cingulum). The results show that the EAR maps are less sensitive to noise than the FA maps and the EAR values change more than the FA values in TLE.

关键词： Tensile stress Magnetic resonance imaging Diffusion tensor imaging Temporal lobe Epilepsy Ear Optical fiber testing Diseases Focusing Medical treatment

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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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Probabilistic Uncertainty Description for an ETFE Estimated Plant using a Sequence of Multi-Sinusoidal Signals

Probabilistic Uncertainty Description for an ETFE Estimated ...

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American control Conference

作者： Richard Steenis Daniel E. Rivera School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ 85287-5706 USA Control Systems Engineering Laboratory School of Mechanical Aerospace Chemical and Materials Engineering Arizona State University Tempe AZ 85287-6106 USA

ISBN: (纸本)9781424474264

This paper generalizes a probabilistic frequency-domain uncertainty description for an Empirical Transfer Function Estimate (ETFE) model developed by Bayard by using an input signal that is composed of a sequence of distinct multi-sinusoidal signals, instead of a single fixed multi-sinusoidal signal. Each signal in the sequence may have different sinusoidal amplitudes, number of signal periods, and fundamental frequency. The corresponding aggregate ETFE plant estimate for the sequence of multi-sinusoidal signals is developed as well. Besides their usefulness for robust control design, the plant and uncertainty expressions enable the use of adaptive algorithms for input signal adjustment during experimental testing in system identification. The use of adaptive signal algorithms also allows the opportunity to improve plant estimates, shape the probabilistic uncertainty description, and reduce input signal duration based on information learned during identification testing. A series of illustrative examples are included to show the relationship between the properties of the multi-sinusoidal signals in the input sequence and the plant uncertainty description.

关键词： Probabilistic Uncertainty Description ETFE Plant Estimation System Identification Robust control Robust control System identification input signal signals Input sequence

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Iterative learning control of a class of fractional order nonlinear systems

Iterative learning control of a class of fractional order no...

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IEEE International Symposium on intelligent control (ISIC)

作者： Yan Li Hyo-Sung Ahn YangQuan Chen School of Control Science and Engineering Shandong University Shandong China Gwangju Institute of Science and Technology Gwangju South Korea Center for Self-Organizing and Intelligent Systems of Department of Electrical and Computer Engineering Utah State University Logan UT USA

This paper firstly addresses the convergence analysis of iterative learning control of a class of fractional order nonlinear systems using the generalized Gronwall-Bellman lemma. Detailed problem definition and conver... 详细信息

关键词： Nonlinear systems Convergence Simulation Fractional calculus Linear systems Differential equations Laplace equations

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Impulse response invariant discretization of a generalized commensurate fractional order filter

Impulse response invariant discretization of a generalized c...

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World Congress on intelligent control and Automation (WCICA)

作者： Yan Li Hu Sheng YangQuan Chen School of Control Science and Engineering Shandong University Jinan China Department of Electronic Engineering Dalian University of Technology Dalian China Center for Self-Organizing and Intelligent Systems (CSOIS) Department of Electrical and Computer Engineering Utah State University Logan UT USA

In this paper, we derive the impulse response of a generalized commensurate fractional-order filter of the form (s 2α +as α +b) -γ , where a, b ≥ 0, α ∈ (0, 1] and γ ∈ (0, 1). The asymptotic properties of the impulse responses are obtained. Moreover, based on the derived analytical impulse response, we show how to perform the discretization of the above fractional-order filter. Finally, a number of illustrated examples in time and frequency domains are provided as proofs of concepts.

关键词： Laplace equations Fractional calculus Frequency response Equations Time frequency analysis Time domain analysis

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Delay-dependent conditions for monotonic convergence of uncertain ILC systems: An LMI approach

Delay-dependent conditions for monotonic convergence of unce...

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IEEE Conference on Decision and control

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division the Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

ISBN: (纸本)9781424477456

This paper deals with the iterative learning control (ILC) problem for uncertain time-delay systems (TDS). In order to ensure monotonic convergence of the ILC process, a sufficient condition is developed using an H ∞ -based framework. It shows that under this framework, the convergence condition is enabled to be delay-dependent and have a formulation in terms of linear matrix inequalities (LMIs). Moreover, formulas for the updating law design can be derived by directly solving LMIs. A numerical example is provided to verify that the delay-dependent condition in LMI forms is effective in producing monotonically convergent ILC algorithms.

关键词： Convergence Symmetric matrices Robustness Delay Uncertainty Performance analysis Linear matrix inequalities

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Spectral clustering of resting state fMRI reveals default mode network with specifically reduced network homogeneity in major depression

Spectral clustering of resting state fMRI reveals default mo...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Alireza Sojoudi Seyed Mohammad Shams Gholam-Ali Hossein-Zadeh Hamid Soltanian-Zadeh Bernhard Bogerts Kolja Schiltz Martin Walter Control & Intelligent Centre of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI USA Department of Psychiatry University of Magdeburg Magdeburg Germany

Although resting state fMRI seems an ideal tool for investigating clinical populations, especially in case of reduced cooperation or tolerance, unbiased methods with high sensitivity for disease relevant pathologies remain to be identified. In this paper, we perform spectral clustering on the mean time series of automated anatomical labeling regions of interest for comparing the resting state networks in healthy volunteers and major depression disorder (MDD) patients. A new network homogeneity measure is suggested as a criterion for evaluating the level of homogeneity in a network. We found reduced network homogeneity specifically within the default mode network in MDD subjects compared to age-matched controls. In contrast to previously proposed methods investigating network homogeneity, we fully relied on data-driven definition of clusters of interest to fill an important gap between ROI based network analyses and those using ICA.

关键词： Smoothing methods

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Conflict detection in terminal area based on modified unscented particle filter

Conflict detection in terminal area based on modified unscen...

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World Congress on intelligent control and Automation (WCICA)

作者： Laihong Hu Fuchun Sun Hualong Xu Huaping Liu Shengheng Zhang Xuejun Zhang State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing China Second Artillery Engineering College Xi'an Shaanxi China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China School of Electronics and Information Engineering Beihang University Beijing China

With increasing air traffic flow, the increasingly complex air traffic situation has raised possibility of conflicts, which requires higher timeliness and accuracy for conflict detection. Based on the rapidly growing air traffic control technologies, such as radars with excellent accuracy, a modified unscented particle filter (MUPF) algorithm is introduced to perform real-time aircraft status estimation. Compared to traditional unscented particle filter (UPF) algorithm, MUPF uses fewer particles and generates higher accuracy, resulting in considerable reduction in amount of computation. The simulation results show that MUPF has higher accuracy than UPF with the same number of particles, and in conflict detection, it also surpass UPF with lower rate of false alert, higher rate of success alert and smaller error.

关键词： Particle filters Accuracy Educational institutions Air traffic control Traffic control Adaptive optics Automation

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Observer-Based L_(2)-L_(infinity) control for a Class of Stochastic systems with Time-Varying Delay

Observer-Based L_(2)-L_(infinity) Control for a Class of Sto...

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2010 49th IEEE Conference on Decision and control

作者： Lin Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424477456

This paper is devoted to the problem of L_(2)-L_(infinity) control for a class of stochastic time-delay systems via observer-based feedback control. The considered observer contains no time-delay. The purpose is to design an observer-based feedback stabilizing controller such that the augmented closed-loop system is stochastically asymptotically stable with a prescribed L_(2)-L_(infinity) performance satisfied. Based on the stochastic stability theory, a delay-dependent sufficient condition is derived in terms of linear matrix inequalities (LMIs). The observer and controller design method is proposed, while the corresponding explicit expression for the observer and controller gain matrices is also given. Finally, numerical examples and simulation results are included to illustrate the effectiveness of the proposed results.

关键词： stochastic systems system clock time varying stability theory Stochastic delay systems controller gain Closed loop systems

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Analysis of Two Robust Learning control Schemes in the Presence of Random Iteration-Varying Noise

Analysis of Two Robust Learning Control Schemes in the Prese...

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American control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper deals with the design problem of robust iterative learning control (ILC), in the presence of noise that is varying randomly from iteration to iteration. Two ILC schemes are considered: one adopts the previous iteration tracking error (PITE) and the other adopts the current iteration tracking error (CITE), in the updating law. For both schemes, the convergence results are obtained by using a frequency-domain approach, and a comparison between them is presented from the viewpoints of the convergence condition, robustness against plant uncertainty, and delay compensation. It shows that sufficient conditions can be derived to bound the tracking error and make its expectation monotonically convergent in the sense of L_(2)-norm, which work effectively with robustness for all admissible plant uncertainties. Furthermore, the sufficient conditions for both schemes can also be formulated in terms of two complementary functions, which do not depend on the delay time as well as the plant uncertainty and, thus, make them convenient to be checked and solved using the frequency-domain tools. Numerical simulations are included to illustrate the effectiveness of the two proposed ILC schemes.

关键词： Iterative learning control monotonic convergence previous iteration tracking error current iteration tracking error random iteration-varying noise delay compensation delay compensation monotone convergence iterative methods Iterative learning control follow error Scheme design problems Delay time Sufficient conditions learning control

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