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Evolving granular classification neural networks

Evolving granular classification neural networks

引用

2009 International Joint Conference on Neural Networks, IJCNN 2009

作者： Leite, Daniel F. Costa Jr., Pyramo Gomide, Fernando Faculty of Electrical and Computer Engineering University of Campinas Brazil Graduate Program in Electrical Engineering Catholic University of Minas Gerais Brazil

ISBN: (纸本)9781424435531

The objective of this study is to introduce the concept of evolving granular neural networks (eGNN) and to develop a framework of information granulation and its role in the online design of neural networks. The suggested eGNN are neural models supported by granule-based learning algorithms whose aim is to tackle classification problems in continuously changing environments. eGNN are constructed from streams of data using fast incremental learning algorithms. eGNN models require a relatively small amount of memory to perform classification tasks. Basically, they try to find information occurring in the incoming data using the concept of granules and T-S neurons as basic processing elements. The main characteristics of eGNN models are continuous learning, self-organization, and adaptation to unknown environments. Association rules and parameters can be easily extracted from its structure at any step during the evolving process. The rule base gives a granular description of the behavior of the system in the input space together with the associated classes. To illustrate the effectiveness of the approach, the paper considers the Iris and Wine benchmark problems. © 2009 IEEE.

关键词： Learning algorithms

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Controller design to regulate the DC voltage of a VSC converter

Controller design to regulate the DC voltage of a VSC conver...

引用

2009 IEEE electrical Power and Energy Conference, EPEC 2009

作者： Hidalgo Mora, Carlos A. Diaz, Nelson L. Universidad Distrital F.J.C. Bogota Colombia Department of Electrical and Computer Engineering Graduate Program in Engineering - Industrial Automation Universidad Nacional de Colombia Bogota Colombia

ISBN: (纸本)9781424445080

The basic function of VSCs is to convert the DC voltage stored in a capacitor into AC voltages or AC voltages into DC voltage. One of the advantages of the VSC is that this kind of electronic converters allow to control the active and reactive power flow with an ac-grid independently. This paper presents a short analysis of the characteristics and dynamic of VSC-HVDC, identification techniques to find transfer function to DC Voltage and Reactive Power in a rectifier station are explored, and finally controller design to regulate the DC voltage is exposed and tested by simulations using Matlab Simulink and its toolbox SimpowerSystems. ©2009 IEEE.

关键词： Reactive power

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Design-dimensioning model for grid-connected photovoltaic systems

Design-dimensioning model for grid-connected photovoltaic sy...

引用

2009 IEEE electrical Power and Energy Conference, EPEC 2009

作者： Hernandez, Johann Diaz, Nelson L. Gordillo, Gerardo Universiudad Nacional de Colombia Bogota Colombia Department of Electrical and Computer Engineering Graduate Program in Engineering - Industrial Automation Universidad Nacional de Colombia Bogota Colombia Universidad Nacional Bogota Colombia

ISBN: (纸本)9781424445080

The main goal in design of grid connected photo voltaic systems is to maximize the energy generation based on local energy requirements, weather conditions, economic and social impact. These factors ought to be taken into account to perform a model that allow design grid-connected photo voltaic systems. In this paper a design-dimensioning model for a small grid-connected photo voltaic systems is developed. This model is based on energy conditions instead of power conditions. There are shown the two main trends that are typically used in the design process and the calculation of the two main components of the system (generator and inverter). An example of the design for a system located in Bogota-Colombia is studied. ©2009 IEEE.

关键词： Design

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System identification of magneto-rheological damper using group method of data handling (GMDH)

System identification of magneto-rheological damper using gr...

引用

2009 6th International Symposium on Mechatronics and its Applications, ISMA 2009

作者： Assaleh, Khaled Shanableh, Tamer Kheil, Yasmeen Abu Department of Electrical Engineering American University of Sharjah United Arab Emirates Department of Computer Science and Engineering American University of Sharjah United Arab Emirates Mechatronics Graduate Program American University of Sharjah United Arab Emirates

ISBN: (纸本)9781424434817

In this paper Group Method of Data Handling (GMDH) technique is implemented and applied to the system identification problem of a Magneto-Rheological (MR) damper. GMDH networks are used to approximate the forward and inverse dynamic behaviors of a MR damper. The difficulty of this identification problem stems from the inherent hysteretic and highly nonlinear dynamics of MR dampers. The GMDH-based solution exhibits comparable identification accuracy in both the forward and inverse models as compared to state-of-the-art more computationally extensive solutions. © 2009 IEEE.

关键词： Inverse problems

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Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle

Fatigue and non-fatigue mathematical muscle models during fu...

引用

作者： Cai, Zhijun Bai, Er-Wei Shield, Richard K. Electrical and Computer Engineering University of Iowa Iowa City IA 52242 United States Graduate Program in Physical Therapy and Rehabilitation Science University of Iowa Iowa City IA 52242 United States

ISBN: (纸本)9783902661494

electrical muscle stimulation demonstrates potential for restoring functional movement and for preventing muscle atrophy after spinal cord injury (SCI). To optimize delivery of electrical stimulation protocols, an accurate and easy-to-implement mathematical skeletal muscle model is essential. The existing models are either accurate but complex, making them hard to implement, such as the Hill-Huxley-type model, or simple but inaccurate, such as second order model. In this paper, we propose a Wiener-Hammerstein system to model the paralyzed skeletal muscle dynamics under electrical stimulus conditions. The proposed model has substantial advantages in identification algorithm analysis and implementation including computational complexity and convergence. Experimental data sets were collected on soleus muscles under 15 Hz frequency stimulation for fourteen subjects with SCI. The simulation results show that the proposed model outperforms the Hill-Huxley-type model not only in peak force prediction, but also in fitting performance for force output of each individual stimulation train. © 2009 IFAC.

关键词： Muscle

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Understanding quantification of microvascularity with high-frequency power Doppler ultrasound

Understanding quantification of microvascularity with high-f...

引用

Medical Imaging 2009: Ultrasonic Imaging and Signal Processing

作者： Pinter, Stephen Z. Lacefield, James C. Biomedical Engineering Graduate Program Departments of Electrical University of Western Ontario London ON Canada Department of Electrical and Computer Engineering University of Western Ontario London ON Canada Department of Medical Biophysics University of Western Ontario London ON Canada Robarts Research Institute University of Western Ontario London ON Canada

ISBN: (纸本)9780819475169

High-frequency power Doppler imaging of angiogenesis can be challenging given the presence of small blood vessels and slow flow velocities. In the presence of substantial Doppler artifacts such as false-positive color pixels or undetected vessels, color pixel density (CPD) and related vascularity metrics do not provide accurate estimates of vascular volume fraction. As a step towards improved microvascular quantification, flow-phantom experiments were performed to establish relationships between CPD and wall filter cut-off velocity for various combinations of vessel size (160, 200, 250, 300, and 360 μm), flow velocity (4, 3, 2, 1, and 0.5 mm/s), and transducer frequency (30 and 40 MHz). Three distinct regions were observed in plots of CPD versus wall filter cut-off velocity: overestimation of CPD at low cut-offs, underestimation of CPD at high cut-offs, and a plateau at intermediate cut-offs. The CPD at the plateau closely matched the phantom's actual vascular volume fraction. The length of the plateau corresponded with the flow-detection performance of the Doppler system, which was assessed using receiver operating characteristic analysis. Color pixel density versus wall filter cut-off curves from analogous in vivo experiments exhibited the same shape, including a distinct CPD plateau. The similar shape of the flow-phantom and in vivo curves suggests that the presence of a plateau can be used to identify the best-estimate CPD value in an in vivo experiment. The ability to identify the best CPD estimate is expected to improve quantification of angiogenesis and anti-angiogenic treatment responses with power Doppler. © 2009 SPIE.

关键词： Flow velocity

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Simulation of Gravity and Flooding Algorithm for Wireless Sensor Network

Simulation of Gravity and Flooding Algorithm for Wireless Se...

引用

IEEE Malaysia International Conference on Communications

作者： Karyono Ihan Martoyo Henri P. Uranus Junita Byungho Kim Graduate and Undergraduate Program in Electrical Engineering University of Pelita Harapan Dept. of Computer Engineering Kyungsung University

ISBN: (纸本)9781424455317;9781424455324

Wireless Sensor Network (WSN) is a network of sensors that has a very large scale of nodes with a tight resources limitation. WSN is application specific, with a wide range of applications in military, survey, industrial, up to home usage. The major problems for WSN are resource limitations and dynamic network, which require unique algorithms for unique applications. Our study focused on the implementation and the characterization of the Gravity algorithm, with the Flooding algorithm as a comparison. The Gravity algorithm uses the gravity weight which is stored on each node to form a virtual contour. This contour will guide the message to reach the sink. This work is the first implementation of the Gravity model in OMNeT++. Simulations conducted in the full mesh and the layered topology show that the Gravity algorithm uses less energy and a higher diversity factor compared to the Flooding algorithm. A similar result is also acquired when the probability of failures are considered. The result shows that the Gravity algorithm outperforms the Flooding algorithm while still maintaining the simplicity of the algorithm. This is important to a WSN which is resources limited. Only a small amount of memory is needed for the gravity weight calculation and storage.

关键词： Wireless Sensor Network OMNeT++ Flooding Gravity Routing Algorithm Wireless sensor networks Gravity Flood Routing algorithms WSN gene gravity model algorithms diversity factor Custom design simulating

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Beam steering performance of electrowetting microprism arrays

Beam steering performance of electrowetting microprism array...

引用

Enabling Photonics Technologies for Defense, Security, and Aerospace Applications V

作者： Han, Wei Haus, Joseph W. Mcmanamon, Paul Heikenfeld, Jason Smith, Neil R. Yang, Jia Electro-Optics Graduate Program University of Dayton 300 College Park Dayton OH 45469-0245 United States Electrical and Computer Engineering Dept. University of Cincinnati Cincinnati OH 45221-0030 United States

ISBN: (纸本)9780819476050

We perform numerical calculations for the diffraction efficiency of single-sided microprism designs with optical beams spread over several microprisms. For small angles (less than 1.5 degrees) the far-field diffraction efficiency exceeds 90% and the far-field angles can be extended to more than 10 degrees with better than 80% diffraction efficiency. For the microprism array the diffraction angles are discrete and the angles between the diffraction peaks can be covered by applying a tilted phase to the input field. ©2009 SPIE.

关键词： Wetting

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Interval-based evolving modeling

Interval-based evolving modeling

引用

IEEE Workshop on Evolving and Self-Developing Intelligent Systems, ESDIS

作者： Daniel F. Leite Pyramo Costa Fernando Gomide Faculty of Electrical and Computer Engineering State University of Campinas-UNICAMP Brazil Graduate Program in Electrical Engineering Catholic University of Minas Gerais Brazil

This paper introduces a granular, interval-based evolving modeling (IBeM) approach to develop system models from a stream of data. IBeM is an evolving rule-based modeling scheme that gradually adapts its structure (information granules and rule base) and rules antecedent and consequent parameters from data (inductive learning). Its main purpose is continuous learning, self-organization, and adaptation to unknown environments. The IBeM approach develops global model of a system using a fast, one-pass learning algorithm, and modest memory requirements. To illustrate the effectiveness of the approach, the paper considers actual time series forecasting applications concerning electricity load and stream flow forecasting.

关键词： Predictive models Load forecasting Mathematical model Power system modeling Chaos Neural networks Demand forecasting Data engineering Data analysis Frequency domain analysis

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Evolving granular classification neural networks

Evolving granular classification neural networks

引用

International Joint Conference on Neural Networks (IJCNN)

关键词： Neural networks Prototypes Neurons Clustering methods Electrochemical machining computer networks Design engineering Association rules Data mining Iris

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