检索结果-内蒙古大学图书馆

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yan Wang Mo Jamshidi P. Neville C. Bales S. Morain Department of Electrical and Computer Engineering and Autonomous Control Engineering (ACE) Center University of New Mexico Albuquerque NM USA The Earth Data Analysis Center (EDAC) University of New Mexico Albuquerque NM USA

This work presents a new application of a data-clustering algorithm in Landsat image classification, which improves on conventional classification methods. Neural networks have been widely used in Landsat image classification because they are unbiased by data distribution. However, they need long training times for the network to get satisfactory classification accuracy. The data-clustering algorithm is based on fuzzy inferences using radial basis functions and clustering in input space. It only passes training data once so it has a short training tune. It can also generate fuzzy classification, which is appropriate in the case of mixed, intermediate or complex cover pattern pixels. This algorithm is applied in the land cover classification of Landsat 7 ETM+ over the Rio Rancho area, New Mexico. It is compared with back-propagation neural network (BPNN) to illustrate its effectiveness and concluded that it can get a better classification using shorter training time.

关键词： Satellites Remote sensing Image classification Neural networks Clustering algorithms Humans Content addressable storage Gaussian distribution Self organizing feature maps Indexing

来源：评论

学校读者我要写书评

暂无评论

Design of a robust and adaptive neural network for flexible AC transmission systems

Design of a robust and adaptive neural network for flexible ...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： F. Rashidi M. Rashidi Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran Iran Hormozgan Regional Electric Company Bandar-Abbas Iran

A neuro-control approach for flexible AC transmission systems (FACTS) based on temporal difference learning based multilayer perceptron neural network (TDMLP) is presented in this paper. The proposed scheme consists of a single neuron network whose input is derived from the active or reactive power or voltage derivation at the power system bus, where the FACTS device (in this case an unified power flow controller) is located. The performance and usefulness of this approach is tested and evaluated using both single-machine infinite-bus and two-machine power system subjected to various transient disturbances. It was found that the new intelligent controller for FACTS exhibits a superior dynamic performance in compensation to the existing classical control schemes. Its simple architecture reduces the computational overhead, thereby real-time implementation.

关键词： Robustness Adaptive systems Neural networks Flexible AC transmission systems Power system transients Power system dynamics Multilayer perceptrons Multi-layer neural network Neurons Reactive power control

来源：评论

学校读者我要写书评

暂无评论

Non linear system identification and control design using adaptive wavelet network

引用

IFAC Proceedings Volumes 2004年第13期37卷 507-512页

作者： H.R. Karimi B. Lohmann B. Moshiri P. Jabehdar Maralani Control and Intelligent Processing Center of Excellence. Department of Electrical and Computer Engineering Faculty of Engineering University of Tehran. Tehran. Iran Institute of Automation University of Bremen Otto-Hahn-Allee NW1 Bremen D-28359 Germany

This paper presents an application of wavelet networks in identification and control design for a class of non-linear dynamical systems. The technique of feedback linearization, supervisory control and H ∞ control are used to design an adaptive control law and also the parameters of the wavelet networks are adapted using a Lyapunov-based design. By some theorems, it will be proved that even in the presence of modelling errors, named network error, the stability of the overall identification scheme and the convergence of the network parameters and the boundedness of the state errors are guaranteed.

关键词： System Identification Supervisory control He control Stability Analysis Wavelet Network.

来源：评论

学校读者我要写书评

暂无评论

Feature selection using genetic algorithm and it's application to face recognition

Feature selection using genetic algorithm and it's applicati...

引用

IEEE Conference on Cybernetics and Intelligent Systems

作者： M.T. Harandi M.N. Ahmadabadi B.N. Araabi C. Lucas Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

A new method for feature selection based on generic algorithm and its application in face recognition is proposed. Simulation results show the superior performance of the proposed algorithm over the eigenface original method. In comparison to evolutionary pursuit method, the proposed method has a faster training phase and the ability of finding and searching more features using our novel fitness function

关键词： Genetic algorithms Face recognition Face detection Humans Principal component analysis Application software Analysis of variance Character recognition Process control Intelligent control

来源：评论

学校读者我要写书评

暂无评论

Clustering-based framework for comparing fMRI analysis methods

Clustering-based framework for comparing fMRI analysis metho...

引用

IEEE International Symposium on Biomedical Imaging

作者： G.-A. Hossein-Zadeh A.-M. Golestani H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is replaced with a feature space and each method considered as a clustering method in the new space. As a result, different methods can be compared by means of a cluster validity measure. The feature space is computed using a non-parametric method (principal component analysis-PCA). Four subjects have been analyzed with three methods and the proposed cluster-based framework has evaluated performance of the methods. The results are identical to those of the modified receiver operating characteristics (ROC). This validates the proposed approach.

关键词： Clustering algorithms Algorithm design and analysis Image analysis Clustering methods Magnetic analysis Testing Accuracy Reproducibility of results Radiology Magnetic resonance

来源：评论

学校读者我要写书评

暂无评论

Multiresolution automatic segmentation of T1-weighted brain MR images

Multiresolution automatic segmentation of T1-weighted brain ...

引用

IEEE International Symposium on Biomedical Imaging

作者： M. Zeydabadi R.A. Zoroofi H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Automatic segmentation of brain tissues is crucial to many medical imaging applications. We use a multi-resolution analysis and a power transform to extend the well-known Gaussian mixture model expectation maximization based algorithm for segmentation of white matter, gray matter, and cerebrospinal fluid from T1-weighted magnetic resonance images (MRI) of the brain. Experimental results with near 4000 synthetic and real images are included. The results illustrate that the proposed method outperforms six existing methods.

关键词： Image resolution Image segmentation Biomedical imaging Multiresolution analysis Image analysis Magnetic analysis Algorithm design and analysis Brain modeling Magnetic liquids Magnetic resonance

来源：评论

学校读者我要写书评

暂无评论

MRSI brain tumor characterization using wavelet and wavelet packets feature spaces and artificial neural networks

MRSI brain tumor characterization using wavelet and wavelet ...

引用

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

作者： A. Yazdan-Shahmorad H. Soltanian-Zadeh R.A. Zoroofi Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for assessing biochemical fingerprint of tissue composition. The need to differentiate between normal and abnormal tissues and determine type of abnormality before biopsy or surgery motivated development and application of MRSI. There are several technical reasons that make the brain easier than other organs to be examined with MRSI. This work presents our proposed methods and results for the analysis of the brain spectra of patients with three tumor types (malignant glioma, astrocytoma, and oligodendroglioma). After extracting features from MRSI data using wavelet and wavelet packets, we use artificial neural networks to determine the abnormal spectra and the type of abnormality. We evaluated the proposed methods using clinical and simulated MRSI data and biopsy results. The MRSI analysis results were correct 97% of the time when classifying the spectra of the clinical MRSI data into normal tissue, tumor, and radiation necrosis. They were correct 72% and 83% of the time when determining tumor types using the clinical and simulated MRSI data, respectively.

关键词： Wavelet packets Neoplasms Artificial neural networks Biopsy Magnetic resonance Spectroscopy Magnetic resonance imaging Fingerprint recognition Surgery Cancer

来源：评论

学校读者我要写书评

暂无评论

Reactive real time behavior for mobile robots in unknown environments

Reactive real time behavior for mobile robots in unknown env...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： B.B.K. Reddy B. Kimiaghalam A. Homaifar NASA Autonomous Control and 1iformation Technology Center (NASA ACIT) Department of Electrical and Computer Engineering North Carolina Agriculture and Technical State University USA

The objective is to emulate the stimulus-response behavior for robot navigation in unknown environments. The robot's objective is to move from its current position to some predefined coordinates, namely, a predefined goal point. The proposed behavior is reactive and the robot has no prior information about the size and location of the obstacles in the environment. This control algorithm is a combination of two main behaviors: wall following and goal seeking, and is based totally on real-time data acquisition from immediate surroundings of the robot. A carefully designed fuzzy inference system (FlS) is used to determine the change in velocity and direction of the robot based on the sonar sensor and inertial cube (Gyro) sensor readings.

关键词： Mobile robots Robot kinematics Robot sensing systems Tactile sensors NASA Inference algorithms Data acquisition Fuzzy systems Sonar navigation Sensor systems

来源：评论

学校读者我要写书评

暂无评论

Activation detection in multi-subject studies of fMRI using GLRT

Activation detection in multi-subject studies of fMRI using ...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.M. Shams G.A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics University of Tehran School of Cognitive Sciences Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System University of Tehran School of Cognitive Sciences Iran

A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data

关键词： Testing Hemodynamics Brain modeling Process control Intelligent control Physics computing Mathematics Time series analysis Magnetic resonance imaging Data analysis

来源：评论

学校读者我要写书评

暂无评论

Electromagnetic fields in the hollow interior region of a monocone antenna

Electromagnetic fields in the hollow interior region of a mo...

引用

Southeastern Symposium on System Theory

作者： S. Giles D.L. Stachowiak G. Adamovsky Electrical Engineering Department Tuskegee University Tuskegee AL USA Electrical Engineering and Computer Science Department University of Tolctlo and Eötvös Lárand University Toledo OH USA Instrumentation and Control Group NASA Glenn Research Center Cleveland OH USA

A thin, hollow, monocone antenna above a ground plane was constructed and studied. The antenna was used to roughly model the convergent region of a rocket exhaust nozzle. The input impedances and currents on the aluminum antenna were measured. The monocone field expansions were found for the exterior and interior regions of the antenna. Mode matching was used to determine the coefficients of expansion with an edge condition applied to the rim of the antenna. After the approximate electric and magnetic fields were found, the associated time-averaged Poynting vector was produced and mapped.

关键词： Electromagnetic fields USA Councils Impedance Frequency Antenna measurements Ground support Instruments NASA Electromagnetic radiation Bandwidth

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：