检索结果-内蒙古大学图书馆

2006 IEEE International Conference on Information Reuse and Integration, IRI-2006

作者： Jamshidi, Mo Department of Electrical and Computer Engineering and Autonomous Control Engineering ACE Center University of Texas San Antonio TX United States IEEE ASME AAAS TWAS NYAS HAE University of Texas San Antonio TX United States Department of Electrical and Computer Engineering Department of Manufacturing Engineering UNM

ISBN: (纸本)0780397886

One of the main challenges of any related paradigms in systems engineering is being able to handle complex systems under unforeseen uncertainties. A system may be called complex if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is so uncertain that classical techniques cannot easily handle the problem. A system of systems (SoS) is a "super system," or an integration of complex systems coordinated together in such a way as to achieve a wider set of goals with possible higher significance such as global warming, Mars missions, air traffic control, global earth observation system, etc. Computational Intelligence or Soft Computing, a consortium of fuzzy logic (approximate reasoning), neuro-computing (learning), genetic algorithms and genetic programming (optimization), has proven to be a powerful set of tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this presentation, paradigms using soft computing approaches are utilized to design autonomous controller with controller reuse for a number of space applications. The notion of adaptation in autonomous controller reuse can be handled via intelligent tools to add on additional capabilities in real-time scenarios. Learning from past experience is but one such scenario for the reuse of autonomous controllers. These applications include satellite array formations, robotic agents and the Virtual Laboratory (V-LAB®) for multi-physics modeling and simulation. A view of the future activities of the NASA JPL for space exploration will also be given. SoS concepts will be described and a few testbed cases will be introduced, including a robotic swarm with dynamic sensor networks for homeland security at UTSA ace Center. Some animated and experimental implementation movies will be shown.

关键词： Systems engineering

来源：评论

学校读者我要写书评

暂无评论

IEEE IRI 2006 Keynote Speech(I);System of Systems - From Definition to Architecture to Simulation to Space Applications

IEEE IRI 2006 Keynote Speech(I);System of Systems - From Def...

引用

IEEE International Conference on Information Reuse and Integration (IRI)

作者： Mo Jamshidi Department of Electrical and Computer Engineering and Autonomous Control Engineering-ACE Center University of Technology San Antonio TX USA

关键词：

来源：评论

学校读者我要写书评

暂无评论

Using gated experts in fault diagnosis and prognosis

Using gated experts in fault diagnosis and prognosis

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： H. Berenji Yan Wang D. Vengerov R. Langari M. Jamshidi NASA Research Park Intelligent Inference Systems Corporation Moffett Field CA USA ECElectrical and Computer Engineering Department atid Autonomous Control Engineering ACE University of New Mexico Albuquerque NM USA Texas A and M University College Station TX USA

Three individual experts have been developed based on extended auto associative neural networks (E-AANN), Kohonen self organizing maps (KSOM), and the radial basis function based clustering (RBFC) algorithms. An integrated method is proposed later to combine the set of individual experts managed by a gated experts algorithm, which assigns the experts based on their best performance regions. We have used a Matlab Simulink model of a chiller system and applied the individual experts and the integrated method to detect and recover sensor errors. It has been shown that the integrated method gets better performance in diagnostics and prognostics compared with each individual expert.

关键词： Fault diagnosis Neural networks Clustering algorithms Self organizing feature maps Pattern recognition Fault detection Intelligent systems NASA control engineering Mathematical model

来源：评论

学校读者我要写书评

暂无评论

A novel auto regression and fuzzy-neural combination method to identify cardiovascular dynamics

A novel auto regression and fuzzy-neural combination method ...

引用

Proceedings of the Biannual World Automation Congress

作者： Jingyu Liu Mo Jamshidi S. Pourbabak Center of Autonomous Control Engineering (ACE) and Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA Department of Internal Medicine University of Massachusetts Worcester MA USA

In this paper cardiovascular dynamics, which refers to the dynamic relationship among the heart rate (HR), arterial blood pressure (ABP) and instantaneous lung volume (ILV), is identified through a novel combination approach that consists of a set of linear auto-regression (AR) equations and nonlinear fuzzy-neural inference. Based on linear assumption of cardiovascular system, auto-regressive and moving average method (ARMA) has been popular approaches to identify the complex cardio-system in recent years. Fuzzy set theory is very suitable to systems with uncertainties such as the cardiovascular dynamic system with expert knowledge. Fuzzy- Neural inference paradigm imports the auto-learning property into fuzzy logic engine, therefore extracts some knowledge from data automatically. An effective hybrid approach, which has parallel modular structure of AR and Fuzzy-neural inference, becomes feasible IO interpret physiologically linear component of heart function and nonlinear nervous regulation component respectively. Details of proposed combination method as well as subjects' study results are presented in this paper.

关键词： Cardiology Heart rate Nonlinear dynamical systems Cardiovascular system Arterial blood pressure Uncertainty Signal analysis Frequency domain analysis Lungs Data mining

来源：评论

学校读者我要写书评

暂无评论

Multispectral Landsat image classification using a data clustering algorithm

Multispectral Landsat image classification using a data clus...

引用

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

Multi-agent simulation using discrete event and soft-computing methodologies

Multi-agent simulation using discrete event and soft-computi...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： P. Sridhar S. Sheikh-Bahaei Shan Xia M. Jamshidi Center for Autonomous Control Engineering (ACE) and Department of Computer Science University of New Mexico Albuquerque NM USA Center for Autonomous Control Engineenng (ACE) and Department of Electncal & ComputerEngmeenng Engmeenng University of New Mexico Albuquerque NM USA Center for Autonomous Control Engineering (ACE) and Department of Electrical & Computer Engineering University of New Mexico Albuquerque NM USA

With the emerging applications of multi-agent systems, there is always a need for simulation to verify the results before actual implementation. Multi-agent simulation provides a test bed for several soft-computing algorithms like fuzzy logic, learning automata, evolutionary algorithms, etc. In this paper we discuss the fusion of these soft-computing methodologies and existing tools for discrete event simulation (DEVS) for multi-agent simulation. We propose a methodology for combining the agent-based architecture, discrete event system and soft-computing methods in the simulation of multi-agent robotics and network security system. We also define a framework called Virtual Laboratory (V-Lab/spl reg/) for multi-agent simulation using intelligent tools.

关键词： Discrete event simulation Multiagent systems Automatic testing Logic testing Fuzzy logic Learning automata Evolutionary computation Discrete event systems Robotics and automation Laboratories

来源：评论

学校读者我要写书评

暂无评论

Time delay and power control in spread spectrum wireless networks

引用

IFAC Proceedings Volumes 2001年第23期34卷 159-164页

作者： Aly I. El-Osery Chaouki Abdallah Mo Jamshidi Autonomous Control Engineering Center (ACE) The University of New Mexico Albuquerque NM 87131 USA Electrical & Computer Engineering Department The University of New Mexico Albuquerque NM 87131 USA

Delay in the computation of the signal-to-interference ratio in communication systems is unavoidable. In the the case of mobile communication, delay is a very critical problem due the fast variation of the communication channel and the need for effective, fast and accurate power control. In this paper we present our approach to dealing with the delay in mobile communication systems as well as our controller to achieve and maintain the desired signal quality. We will concentrate on the code division multiple access (CDMA) systems.

关键词： Power control CDMA

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial

引用

Intelligent Automation & Soft Computing 2000年第3期6卷 171-172页

作者： Mohamed Kamel[a] & Mohammad Jamshidi[b] [a] Pattern Analysis and Machine Intelligence Lab Department of Systems Design Engineering University of Waterloo Waterloo Ontario N2L 3G1 Canada [b] Nasa Center for Autonomous Control Engineering and Department of Electrical and Computer Engineering The University of New Mexico Albuquerque NM 87131 USA http://ace.tmm.edu

Click to increase image sizeClick to decrease image size

关键词：

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：