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检索条件"主题词=Optimization Algorithms"

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Independent Component Analysis of EEG-fMRI data for studying epilepsy and epileptic seizures

Independent Component Analysis of EEG-fMRI data for studying...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Tiziana Franchin Maria G. Tana Vittorio Cannata Sergio Cerutti Anna M. Bianchi Clinical-Technological Innovations Research Unit Bambino Gesu Children's Hospital and Research

ISBN: (纸本)9781457702150

Here we present a method for classifying fMRI independent components (ICs) by using an optimized algorithm for the individuation of noisy signals from sources of interest. The method was applied to estimate brain activations from combined EEG-fMRI data for the exploration of epilepsy. Spatial ICA was performed using the above-mentioned optimized algorithm and other three popular algorithms. ICs were sorted considering the value: of the coefficients of determination R2, obtained from the multiple regression analysis with morphometric maps of cerebral matter;of the kurtosis, which features the signal energy. The validation of the method was performed comparing the brain activations obtained with those resulted using the General Linear Model (GLM). The ICA-derived activations in different datasets comprised subareas of the GLM-revealed activations, even if the volume and the shape of activated areas do not correspond exactly. The method proposed also detects additional negative regions implicated in a default mode of brain activity, and not clearly identified by GLM. Compared with a traditional GLM approach, the ICA one provides a flexible way to analyze fMRI data that reduces the assumptions placed upon the hemodynamic response of the brain and the temporal constrains.

关键词： optimization algorithms epileptic seizure Cerebrum signal energy Individuation Epilepsy Integrated circuits kurtosis brain activity fMRI

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Heterogeneous Visual Features Fusion via Sparse Multimodal Machine

Heterogeneous Visual Features Fusion via Sparse Multimodal M...

引用

IEEE Conference on Computer Vision and Pattern Recognition

作者： Hua Wang Feiping Nie Heng Huang Chris Ding Department of Electrical Engineering and Computer Science Colorado School of Mines Department of Computer Science and Engineering University of Texas at Arlington

ISBN: (纸本)9781467364102

To better understand, search, and classify image and video information, many visual feature descriptors have been proposed to describe elementary visual characteristics, such as the shape, the color, the texture, etc. How to integrate these heterogeneous visual features and identify the important ones from them for specific vision tasks has become an increasingly critical problem. In this paper, We propose a novel Sparse Multimodal Learning (SMML) approach to integrate such heterogeneous features by using the joint structured sparsity regularizations to learn the feature importance of for the vision tasks from both group-wise and individual point of views. A new optimization algorithm is also introduced to solve the non-smooth objective with rigorously proved global convergence. We applied our SMML method to five broadly used object categorization and scene understanding image data sets for both single-label and multi-label image classification tasks. For each data set we integrate six different types of popularly used image features. Compared to existing scene and object categorization methods using either single modality or multi-modalities of features, our approach always achieves better performances measured.

关键词： Visualization video information Integrate image feature Religious Missions global convergence optimization algorithms Sight

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ROLLING SHUTTER CORRECTION FOR VIDEO WITH LARGE DEPTH OF FIELD

ROLLING SHUTTER CORRECTION FOR VIDEO WITH LARGE DEPTH OF FIE...

引用

IEEE International Conference on Image Processing

作者： Yen-Hao Chiao Tung-Ying Lee Shang-Hong Lai Dept. of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9781479923427

Rolling shutter correction has attracted considerable attention in recent years. Several algorithms have been proposed to correct the distortion. Previous methods on rolling shutter correction did not consider depth variations in the scene. In this work, we overcome the limitation of the previous works that the depth of field in the scene is small. We present a correction model for rectifying the rolling shutter video based on the depth maps estimated from the rolling shutter video. In addition, we propose a two-stage optimization algorithm to estimate the temporal camera motion and the associated depth maps. Experimental results show the improvement of the proposed rolling shutter correction algorithm that takes the depth information into account.

关键词： Rolling shutter correction Depth estimation Camera motion estimation rolling shutter Videotapes DEPTH OF FIELD motion estimation STRUCTURE MAP optimization algorithms SCROLL

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Optimal Aperture Distribution of Near-Field Antennas for Maximum Signal Penetration

Optimal Aperture Distribution of Near-Field Antennas for Max...

引用

European Conference on Antennas and Propagation

作者： Aidin Razavi Jian Yang Tomas McKelvey Dept. of Signals and Systems Chalmers University of Technology

ISBN: (纸本)9781467321877

We present an investigation on the optimal aperture, both its size and current source distribution, for the maximum penetration of signals in near-field applications. The near-field beam radius is calculated for different size of the uniform Huygen's source distribution so that the optimal size of a uniform Huygen aperture is concluded. For a general aperture distribution, both analytical methods and optimization algorithm are applied.

关键词： Optimal near-field aperture Near-field beam radius Maximum penetration ferrite antenna apertures near-field Current sources signals optimization algorithms ANTENNA Optimal

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Automatic Design of IMA Systems

Automatic Design of IMA Systems

引用

IEEE Aerospace Conference

作者： Uwe Salomon Reinhard Reichel Institute of Aircraft Systems University of Stuttgart 70569 Stuttgart Germany +49-163-4691530 Institute of Aircraft Systems University of Stuttgart 70569 Stuttgart Germany +49-711-685-67090

ISBN: (纸本)9781467318129

During the last years, the integrated modular avionics (IMA) design philosophy became widely established at air-craft manufacturers, giving rise to a series of new design challenges, most notably the allocation of avionics functions to the various IMA components and the placement of this equipment in the aircraft. This paper presents a modelling approach for avionics that allows automation of some steps of the design process by applying an optimisation algorithm which searches for system configurations that fulfil the safety requirements and have low costs. The algorithm was implemented as a quite so-phisticated software prototype, therefore we will also present detailed results of its application to actual avionics systems.

关键词： series of new design challenges allocation IMA avionics allocation safety requirements Software prototyping design process Computer-Aided Design optimization algorithms updated design Automation Aircraft Remainder of a Series Telescoping a series

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Hybrid sparse regularization for Magnetic Resonance Spectroscopy

Hybrid sparse regularization for Magnetic Resonance Spectros...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Andrea Laruelo Lotfi Chaari Hadj Batatia Soleakhena Ken Ben Rowland Anne Laprie Jean-Yves Tourneret Institut Claudius Regaud Toulouse F-31052 France

ISBN: (纸本)9781457702150

Magnetic resonance spectroscopy imaging (MRSI) is a powerful non-invasive tool for characterising markers of biological processes. This technique extends conventional MRI by providing an additional dimension of spectral information describing the abnormal presence or concentration of metabolites of interest. Unfortunately, in vivo MRSI suffers from poor signal-to-noise ratio limiting its clinical use for treatment purposes. This is due to the combination of a weak MR signal and low metabolite concentrations, in addition to the acquisition noise. We propose a new method that handles this challenge by efficiently denoising MRSI signals without constraining the spectral or spatial profiles. The proposed denoising approach is based on wavelet transforms and exploits the sparsity of the MRSI signals both in the spatial and frequency domains. A fast proximal optimization algorithm is then used to recover the optimal solution. Experiments on synthetic and real MRSI data showed that the proposed scheme achieves superior noise suppression (SNR increase up to 60%). In addition, this method is computationally efficient and preserves data features better than existing methods.

关键词： Magnetic Resonance Spectroscopy wavelet transforms Noise reduction optimization algorithms Noise suppression

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DETERMINING THE OPTIMAL SAMPLING SET SIZE FOR RANDOM SEARCH 13

DETERMINING THE OPTIMAL SAMPLING SET SIZE FOR RANDOM SEARCH

引用

Simulation Conference

作者： Chenbo Zhu Jie Xu Chun-Hung Chen Loo Hay Lee Jianqiang Hu Fudan University Shanghai China George Mason University Fairfax Virginia National University of Singapore Singapore

ISBN: (纸本)9781479920778

Random search is a core component of many well known simulation optimization algorithms such as nested partition and COMPASS. Given a fixed computation budget, a critical decision is how many solutions to sample from a search area, which directly determines the number of simulation replications for each solution assuming that each solution receives the same number of simulation replications. This is another instance of the exploration vs. exploitation tradeoff in simulation optimization. Modeling the performance profile of all solutions in the search area as a normal distribution, we propose a method to (approximately) optimally determine the size of the sampling set and the number of simulation replications and use numerical experiments to demonstrate its performance.

关键词： Solutions simulating optimization algorithms compasses Gaussian distribution numerical invariant Core Assembly

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Sampling-based Learning Control for Quantum Systems with Hamiltonian Uncertainties

Sampling-based Learning Control for Quantum Systems with Ham...

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IEEE Annual Conference on Decision and Control

作者： Daoyi Dong Chunlin Chen Ruixing Long Bo Qi Ian R. Petersen School of Information Technology and Electrical Engineering University of New South Wales at the Australian Defence Force Academy Canberra ACT 2600 Australia Department of Control and System Engineering Nanjing University Nanjing 210093 China Department of Chemistry Princeton University Princeton New Jersey 08544 USA Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467357159

Robust control design for quantum systems has been recognized as a key task in the development of practical quantum technology. In this paper, we present a systematic numerical methodology of sampling-based learning control (SLC) for control design of quantum systems with Hamiltonian uncertainties. The SLC method includes two steps of "training" and "testing and evaluation". In the training step, an augmented system is constructed by sampling uncertainties according to possible distributions of uncertainty parameters. A gradient flow based learning and optimization algorithm is adopted to find the control for the augmented system. In the process of testing and evaluation, a number of samples obtained through sampling the uncertainties are tested to evaluate the control performance. Numerical results demonstrate the success of the SLC approach. The SLC method has potential applications for robust control design of quantum systems.

关键词： design control learning control quanta AUGMENTED SYSTEM Uncertainty Gradient flow Hamiltonian control performance Robust control optimization algorithms

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A Set-Based Discrete Differential Evolution Algorithm

A Set-Based Discrete Differential Evolution Algorithm

引用

IEEE International Conference on Systems, Man, and Cybernetics

作者： Yu Liu Wei-Neng Chen Zhi-Hui Zhan Ying Lin Yue-Jiao Gong Jun Zhang Department of Computer Science Sun Yat-sen University Key Laboratory of Machine Intelligence and Sensor Network Ministry of Education Key Laboratory of Software Technology Education Department of Guangdong Province P.R. China

ISBN: (纸本)9781479906505

The TSP problem is considered as classical discrete optimization grouping problem, which is widely used in practice, but it is real a difficult NP problem. Simultaneously differential evolution (DE) algorithm has been proven to be a powerful optimization algorithm. Since the mutation process of DE contains a series of arithmetic operators operating on continuous space, few algorithms based on DE solve this problem nicely and the advantages of DE in continuous space cannot be used to solve TSP. To take full advantages of the strengths of DE, this paper proposes a set-based DE (S-DE) which completely follows the procedure of the original DE. We present a representation scheme to characterize the discrete problem space and by redefining its basic concept and all related operators in mutation, DE can operate directly on the original set space of the discrete optimization problems instead of performing a space transformation. In that way, the searching features of DE in continuous space is kept. In experiment, we test the performance of our proposed S-DE and the results show it is very promising.

关键词： component Discrete Differential algorithm Sebased COP TSP MT CARD16 gene discrete element optimization algorithms Total suspended particles evolutionary algorithm arithmetic operator NP problem CONTINUOUS SPACE differential evolution algorithms

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Global Output-Feedback Extremum Seeking Control via Monitoring Functions

Global Output-Feedback Extremum Seeking Control via Monitori...

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IEEE Annual Conference on Decision and Control

作者： Nerito Oliveira Aminde Tiago Roux Oliveira Liu Hsu Dept. of Electrical Engineering Federal University of Rio de Janeiro (COPPE/UFRJ) Brazil Dept. of Electronics and Telecom. Engineering State University of Rio de Janeiro (DETEL/UERJ) Brazil

ISBN: (纸本)9781467357159

This paper addresses the design of an extremumseeking controller based on monitoring function for a class of single-input-single-output (SISO) uncertain nonlinear systems. We demonstrate that it is possible to achieve an arbitrarily small neighborhood of the desired optimal point using only output-feedback. The key idea is the combination of a monitoring function with a norm state observer. We show that, as an important advantage, the proposed scheme achieves the extremum of a unknown nonlinear mapping for all domain of initial conditions, i.e., the real-time optimization algorithm has global convergence/stability properties. Moreover, some tuning rules are given to achieve convergence to global maximum in the presence of local extrema. A numerical example illustrates the viability of the proposed approach.

关键词： Global Maximum optimization algorithms INITIAL CONDITIONS Converge Viability Uncertain nonlinear system

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