IEEE Organizations related to Brownian Motion

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Conferences related to Brownian Motion

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 American Control Conference (ACC)

The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will

  • 2019 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2018 Annual American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2017 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2016 American Control Conference (ACC)

    Control systems theory and practice. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2015 American Control Conference (ACC)

    control theory, technology, and practice

  • 2014 American Control Conference - ACC 2014

    All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano- and micro-systems.

  • 2013 American Control Conference (ACC)

    Control systems theory and practice. Conference themes on sustainability, societal challenges for control, smart healthcare systems. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2012 American Control Conference - ACC 2012

    All areas of control engineering and science.

  • 2011 American Control Conference - ACC 2011

    ACC provides a forum for bringing industry and academia together to discuss the latest developments in the area of Automatic Control Systems, from new control theories, to the advances in sensors and actuator technologies, and to new applications areas for automation.

  • 2010 American Control Conference - ACC 2010

    Theory and practice of automatic control

  • 2009 American Control Conference - ACC 2009

    The 2009 ACC technical program will cover new developments related to theory, application, and education in control science and engineering. In addition to regular technical sessions the program will also feature interactive and tutorial sessions and preconference workshops.

  • 2008 American Control Conference - ACC 2008

  • 2007 American Control Conference - ACC 2007

  • 2006 American Control Conference - ACC 2006 (Silver Anniversary)

  • 2005 American Control Conference - ACC 2005

  • 2004 American Control Conference - ACC 2004

  • 2003 American Control Conference - ACC 2003

  • 2002 American Control Conference - ACC 2002

  • 2001 American Control Conference - ACC 2001

  • 2000 American Control Conference - ACC 2000

  • 1999 American Control Conference - ACC '99

  • 1998 American Control Conference - ACC '98

  • 1997 American Control Conference - ACC '97

  • 1996 13th Triennial World Congress of the International Federation of Automatic Control (IFAC)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Plasma Science (ICOPS)

IEEE International Conference on Plasma Science (ICOPS) is an annual conference coordinated by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear & Plasma Sciences Society.


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Periodicals related to Brownian Motion

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Most published Xplore authors for Brownian Motion

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Xplore Articles related to Brownian Motion

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Queuing and Performance Evaluation of Telecommunication Networks under Traffic Self‐Similarity Conditions

Self-Similar Processes in Telecommunications, None

This chapter contains sections titled:Traffic Fractality Influence Estimate on Telecommunication Network QueuingEstimate of Voice Traffic Self‐Similarity Effects on the IP Networks Input Parameter OptimizationTelecommunication Network Parameters Optimization Using the Tikhonov Regularization ApproachEstimation of the Voice Traffic Self‐Similarity Influence on QoS with Frame Relay NetworksBandwidth Prediction in Telecommunication NetworksCongestion Control of Self‐Similar TrafficReferences


Estimation and Simulation of Network Delay Traces for VoIP in Service Overlay Network

2007 International Symposium on Signals, Systems and Electronics, 2007

The network delay is one of the most important impairments for VoIP (voice over IP). This paper focuses on the bi-objective optimization problem of minimizing sampling cost and also minimizing the error in the estimation of the actual delay traces. We also analyze the real network delay measurements and the simulated network delay trace for fractional Brownian motion (fBm) traffic. ...


Long-correlation image models for textures with circular and elliptical correlation structures

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001

A class of random field model having long-correlation characteristic is introduced. Unlike earlier approaches in long-correlation models, the correlation structure is isotropic or elliptical in this new class of random field model. A comprehensive three-step algorithm for parameter estimation is developed, and the validity of the model is demonstrated with real textures.


Modelling Flow Trajectories Using Fractional Brownian Motion

2010 International Workshop on Chaos-Fractal Theories and Applications, 2010

An improved fractional Brownian motion (fBm) model using fractal geometry is outlined Brownian motion. It produces more realistic flow trajectories than traditional Brownian motion does. The fBm model is used for producing both super diffusive and sub diffusive particle paths, therefore, the non-Fickian diffusion of particle clouds can be modelled. The particle trajectories and clouds are released in an idealised ...


Control of some linear stochastic systems with a fractional Brownian motion

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009

In this paper a control problem for a linear stochastic system driven by a fractional Brownian motion with a cost functional that is quadratic in the state and the control is considered. An optimal control is given explicitly using fractional calculus and the control is shown to depend on the prediction of the fractional Brownian motion as well as the ...


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Educational Resources on Brownian Motion

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IEEE-USA E-Books

  • Queuing and Performance Evaluation of Telecommunication Networks under Traffic Self‐Similarity Conditions

    This chapter contains sections titled:Traffic Fractality Influence Estimate on Telecommunication Network QueuingEstimate of Voice Traffic Self‐Similarity Effects on the IP Networks Input Parameter OptimizationTelecommunication Network Parameters Optimization Using the Tikhonov Regularization ApproachEstimation of the Voice Traffic Self‐Similarity Influence on QoS with Frame Relay NetworksBandwidth Prediction in Telecommunication NetworksCongestion Control of Self‐Similar TrafficReferences

  • Estimation and Simulation of Network Delay Traces for VoIP in Service Overlay Network

    The network delay is one of the most important impairments for VoIP (voice over IP). This paper focuses on the bi-objective optimization problem of minimizing sampling cost and also minimizing the error in the estimation of the actual delay traces. We also analyze the real network delay measurements and the simulated network delay trace for fractional Brownian motion (fBm) traffic. We find that a shifted Gamma distribution models the network delay marginal distribution very well. The simulation based on the simulated network delay trace shows that our novel optimal sampling strategy can obtain a 20 dB signal to noise ratio (SNR) in measurement accuracy at as low as 1.3 HZ sampling frequency.

  • Long-correlation image models for textures with circular and elliptical correlation structures

    A class of random field model having long-correlation characteristic is introduced. Unlike earlier approaches in long-correlation models, the correlation structure is isotropic or elliptical in this new class of random field model. A comprehensive three-step algorithm for parameter estimation is developed, and the validity of the model is demonstrated with real textures.

  • Modelling Flow Trajectories Using Fractional Brownian Motion

    An improved fractional Brownian motion (fBm) model using fractal geometry is outlined Brownian motion. It produces more realistic flow trajectories than traditional Brownian motion does. The fBm model is used for producing both super diffusive and sub diffusive particle paths, therefore, the non-Fickian diffusion of particle clouds can be modelled. The particle trajectories and clouds are released in an idealised coastal bay and the fBm particle tracking method is used for simulation the particle cloud spreading in the bay. There is a noticeable increase in the spreading rate of the cloud. The variation of the Hurst exponent can lead to an area of the flow being affected by a contaminant cloud which is not picked up by the regular Brownian motion models. Using the fBm particle tracking model allows more flexibility in simulation of diffusion in fluids.

  • Control of some linear stochastic systems with a fractional Brownian motion

    In this paper a control problem for a linear stochastic system driven by a fractional Brownian motion with a cost functional that is quadratic in the state and the control is considered. An optimal control is given explicitly using fractional calculus and the control is shown to depend on the prediction of the fractional Brownian motion as well as the usual linear feedback control for the linear-quadratic control problem.

  • Estimation of fractional Brownian motion embedded in a noisy environment using nonorthogonal wavelets

    We show that nonorthogonal wavelets can characterize the fractional Brownian motion (fBm) that is in white noise. We demonstrate the point that discriminating the parameter of fBm from that of noise is equivalent to discriminating the composite singularity formed by superimposing a peak singularity on a Dirac singularity. We characterize the composite singularity by formalizing this problem as a nonlinear optimization problem. This yields our parameter estimation algorithm. For fractal signal estimation, Wiener filtering is explicitly formulated as a function of the signal and noise parameters and the wavelets. We show that the estimated signal is a 1/f process. Comparative studies through numerical simulations of our methods with those of Wornell and Oppenheim (1992) are presented.

  • On the correlation structure of the wavelet coefficients of fractional Brownian motion

    Shows that the interdependence of the discrete wavelet coefficients of fractional Brownian motion, defined by normalized correlation, decays exponentially fast across scales and hyperbolically fast along time.<>

  • Peculiarities of stochastic processes with fractal properties and their applications in problems of navigation information processing

    The model of random process with the memory in the form of fractional Brownian motion is offered. The estimation problem definition and its solution within the Bayesian approach for processing the random processes with memory is given in relation to the navigation problems. The application of filtering to the scalar process of fractional Brownian motion is shown by means of the optimum non-recurrent linear filter and the Kalman filter on the example.

  • The maximum drawdown of the Brownian motion

    The MDD is defined as the maximum loss incurred from peak to bottom during a specified period of time. It is often preferred over some of the other risk measures because of the tight relationship between large drawdowns and fund redemptions. Also, a large drawdown can even indicate the start of a deterioration of an otherwise successful trading system, for example due to a market regime switch. Overall, the MDD is a very important risk measure. To be able to use it more insightfully, its analytical properties have to be understood. As a step towards this direction, we have presented in this article some analytic results that we have developed. We hope more and more results will come out from the research community analyzing this important measure.

  • Scattering from a natural surface described by the fractional Brownian motion model: small perturbation method

    Use of the fractional Brownian motion surface model within the small perturbation scattering model is explored. A new formulation of the normalised radar cross section of natural surfaces is obtained. The effectiveness of the presented model has been assessed by direct comparison with some widespread scattering models and with a set of measured data reported in literature.



Standards related to Brownian Motion

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Jobs related to Brownian Motion

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