Conferences related to Differential equations

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2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Early Vision and Sensors Color, Illumination and Texture Segmentation and Grouping Motion and TrackingStereo and Structure from Motion Image -Based Modeling Physics -Based Modeling Statistical Methods and Learning in VisionVideo Surveillance and Monitoring Object, Event and Scene Recognition Vision - Based Graphics Image and Video RetrievalPerformance Evaluation Applications


2018 14th IEEE International Conference on Signal Processing (ICSP)

ICSP2018 includes sessions on all aspects of theory, design and applications of signal processing. Prospective authors are invited to propose papers in any of the following areas, but not limited to: A. Digital Signal Processing (DSP)B. Spectrum Estimation & ModelingC. TF Spectrum Analysis & WaveletD. Higher Order Spectral AnalysisE. Adaptive Filtering &SPF. Array Signal ProcessingG. Hardware Implementation for Signal ProcessingH Speech and Audio CodingI. Speech Synthesis & RecognitionJ. Image Processing & UnderstandingK. PDE for Image ProcessingL.Video compression &StreamingM. Computer Vision & VRN. Multimedia & Human-computer InteractionO. Statistic Learning & Pattern RecognitionP. AI & Neural NetworksQ. Communication Signal processingR. SP for Internet and Wireless CommunicationsS. Biometrics & AuthentificationT. SP for Bio-medical & Cognitive ScienceU


2018 22nd International Microwave and Radar Conference (MIKON)

Antenna Design, Modeling & MeasurementsMicrowave Devices, Circuits & ComponentsMillimeter-wave & Terahertz TechnologyMicrowave Photonics, Circuits & SystemsRF, VHF & UHF TechnologyEM Field Theory & Numerical TechniquesMicrowave MeasurementsIndustrial, Scientific and Medical ApplicationsWireless Technology & ApplicationsElectromagnetic CompatibilitySpace & Satellite SystemsRadar TechnologyRadar Systems & ApplicationsRadar Signal ProcessingTracking & Data FusionRadar Imaging & Remote SensingNoise, MIMO & UWB RadarsMultistatic & Passive Radar Systems


2018 26th Signal Processing and Communications Applications Conference (SIU)

The general scope of the conference ranges from signal and image processing to telecommunication, and applications of signal processing methods in biomedical and communication problems.

  • 2017 25th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing and Communication Applications (SIU) conference is the most prominent scientific meeting on signal processing in Turkey bringing together researchers working in signal processing and communication fields. Topics include but are not limited to the areas of research listed in the keywords.

  • 2016 24th Signal Processing and Communication Application Conference (SIU)

    Signal Processing Theory, Statistical Signal Processing, Nonlinear Signal Processing, Adaptive Signal Processing, Array and Multichannel Signal Processing, Signal Processing for Sensor Networks, Time-Frequency Analysis, Speech / Voice Processing and Recognition, Computer Vision, Pattern Recognition, Machine Learning for Signal Processing, Human-Machine Interaction, Brain-Computer Interaction, Signal-Image Acquisition and Generation, image Processing, video Processing, Image Printing and Presentation, Image / Video / Audio browsing and retrieval, Image / Video / Audio Watermarking, Multimedia Signal Processing, Biomedical Signal Processing and Image Processing, Bioinformatics, Biometric Signal-Image Processing and Recognition, Signal Processing for Security and Defense, Signal and Image Processing for Remote Sensing, Signal Processing Hardware, Signal Processing Education, Radar Signal Processing, Communication Theory, Communication Networks, Wireless Communications

  • 2015 23th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing Theory Statistical Signal Processing Nonlinear Signal Processing Adaptive Signal Processing Array and Multichannel Signal Processing Signal Processing for Sensor Networks Time-Frequency Analysis Speech / Voice Processing and Recognition Computer Vision Pattern Recognition Machine Learning for Signal Processing Human-Machine Interaction Brain-Computer Interaction Signal-Image Acquisition and Generation image Processing video Processing Image Printing and Presentation Image / Video / Audio browsing and retrieval Image / Video / Audio Watermarking Multimedia Signal Processing Biomedical Signal Processing and Image Processing Bioinformatics Biometric Signal-Image Processing and Recognition Signal Processing for Security and Defense Signal and Image Processing for Remote Sensing Signal Processing Hardware Signal Processing Education Radar Signal Processing Communication Theory Communication Networks Wireless Communications

  • 2014 22nd Signal Processing and Communications Applications Conference (SIU)

    SIU will be held in Trabzon, Turkey at the Karadeniz Technical University Convention and Exhibition Centre on April 23, 2014. SIU is the largest and most comprehensive technical conference focused on signal processing and its applications in Turkey. Last year there were 500 hundred participants. The conference will feature renowned speakers, tutorials, and thematic workshops. Topics include but are not limited to: Signal Procesing, Image Processing, Communication, Computer Vision, Machine Learning, Biomedical Signal Processing,

  • 2013 21st Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2012 20th Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2011 19th Signal Processing and Communications Applications Conference (SIU)

    Conference will bring together academia and industry professionals as well as students and researchers to present and discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. The Conference will also include invited lectures, tutorials and special sessions.

  • 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU)

    S1.Theory of Signal-Processing S2.Statistical Signal-Processing S3.Multimedia Signal-Processing S4.Biomedical Signal-Processing S5.Sensor Networks S6.Multirate Signal-Processing S7.Pattern Recognition S8.Computer Vision S9.Adaptive Filters S10.Image/Video/Speech Browsing, Retrieval S11.Speech/Audio Coding S12.Speech Processing S13.Human-Machine Interfaces S14.Surveillance Signal Processing S15.Bioinformatics S16.Self-Learning S17.Signal-Processing Education S18.Signal-Processing Systems S1

  • 2009 IEEE 17th Signal Processing and Communications Applications Conference (SIU)

    The scope of the conference is to cover recent topics in theory and applications of Signal Processing and Communications.

  • 2008 IEEE 16th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing, Image Processing, Speech Processing, Pattern Recognition, Human Computer Interaction, Communication, Video and Speech indexing, Computer Vision, Biomedical Signal Processing

  • 2007 IEEE 15th Signal Processing and Communications Applications (SIU)

  • 2006 IEEE 14th Signal Processing and Communications Applications (SIU)

  • 2005 IEEE 13th Signal Processing and Communications Applications (SIU)

  • 2004 IEEE 12th Signal Processing and Communications Applications (SIU)


2018 40th Annual International Conference of the IEEE Engineering in Medicine and 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


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Periodicals related to Differential equations

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


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Most published Xplore authors for Differential equations

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Xplore Articles related to Differential equations

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Hard limit induced oscillations

[{u'author_order': 1, u'affiliation': u'Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA', u'full_name': u'X. Jiang'}, {u'author_order': 2, u'affiliation': u'Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA', u'full_name': u'H. Schattler'}, {u'author_order': 3, u'affiliation': u'Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA', u'full_name': u'J. Zaborszky'}, {u'author_order': 4, u'full_name': u'V. Venkatasubramanian'}] Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on, None

This paper reports on the latest developments in taxonomy theory originally developed for dynamic systems represented by ordinary differential equations constrained by algebraic equations (DAEs). It gives some new results on the behavior of a second order state constrained system. It shows that the interplay between an unstable system and the hard limit can result generically in stable non-smooth limit ...


Numerical Simulation of Coal Water Mixture Pipeline Transport Axial Flow Field

[{u'author_order': 1, u'affiliation': u'Sch. of Chem. & Environ. Eng., China Univ. of Min. & Technol., Beijing', u'full_name': u'Zhiqiang Xu'}, {u'author_order': 2, u'affiliation': u'Sch. of Chem. & Environ. Eng., China Univ. of Min. & Technol., Beijing', u'full_name': u'Yuming Xia'}] 2008 International Conference on Computer Science and Information Technology, None

The finite element method is applied to simulate the coal water mixture pipeline transport axial flow field. The pipeline axial velocity and contour distribution are obtained by solving the divided pipeline axial flow field. The relationship curves between the axial velocity and the cross sectional radiuses of the pipeline axial flow field are drawn. Two groups of comparative computations are ...


A geometric approach to the investigation of the dynamics of constrained robotic systems

[{u'author_order': 1, u'affiliation': u'Thomas Jefferson University/Medical Physics Division, Philadelphia, PA, USA', u'full_name': u'I. M. Buzurovic'}, {u'author_order': 2, u'affiliation': u'University of Belgrade, School of Mechanical Engineering/Automatic Control Department, Belgrade, Serbia', u'full_name': u'D. Lj. Debeljkovic'}] IEEE 8th International Symposium on Intelligent Systems and Informatics, None

Medical-technical robotic systems are typical examples in which external contact forces on a system play an important role in the system dynamics. Mathematical modeling of these systems is challenging due to a variety of reasons. Mathematical models for the described class of systems contain differential equations with an associate algebraic equation, which outlines constrained system dynamics. Such a system is ...


On the nonlinear dynamics of fast filtering algorithms

[{u'author_order': 1, u'affiliation': u'Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA', u'full_name': u'C. I. Byrnes'}, {u'author_order': 2, u'full_name': u'A. Lindquist'}, {u'author_order': 3, u'full_name': u'Y. Zhon'}] [1992] Proceedings of the 31st IEEE Conference on Decision and Control, None

A fundamental open problem in linear filtering and estimation is addressed, i.e. what is the steady-state or asymptotic behavior of the Kalman filter, or the Kalman gain, when the observed stationary stochastic process is not generated by a finite-dimensional stochastic system, or when it is generated by a stochastic system having higher dimensional unmodeled dynamics? For a scalar observation process, ...


Solving Riccati differential equations with multilayer neural networks

[{u'author_order': 1, u'affiliation': u'Dept. of Electr. Eng., Erlangen-Nurnberg Univ., Germany', u'full_name': u'Shouling He'}, {u'author_order': 2, u'full_name': u'K. Reif'}, {u'author_order': 3, u'full_name': u'R. Unbehauen'}] Proceedings of the 36th IEEE Conference on Decision and Control, None

The tangential linearisation along the solution curve in a state space has been proposed for solving the feedback stabilisation of a nonlinear system. With the technique a nonlinear control problem can be transferred into a linear time-varying one. However, the Riccati differential equation for the optimal control of the linearised system is not only time dependent, but also the state ...


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Educational Resources on Differential equations

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eLearning

No eLearning Articles are currently tagged "Differential equations"

IEEE-USA E-Books

  • Markov Analysis: Repairable Systems

    This chapter introduces applications of Markov Analysis to repairable systems and illustrated both dynamic and steady-state responses for repairable systems with dif¿¿ferent configurations. Table 11.1 and Table 11.2 summarize the reliability character¿¿istics for the different configurations we considered.

  • Linear Optimal Filters and Predictors

    Estimation problem is the problem of estimating the state of a linear stochastic system by using measurements that are linear functions of the state. The Wiener filter is defined for stationary systems in continuous time, and the Kalman filter is defined for either stationary or nonstationary systems in either discrete time or continuous time, but with finite-state dimension. A brief discussion of solution methods for the Riccati differential equation for the Kalman-Bucy filter is presented in this chapter. An analogous treatment of the discrete-time problem for the Kalman filter is also presented. Prediction is equivalent to filtering when measurements (system outputs) are not available. The chapter gives the implementation equations for continuous-time and discrete-time predictors. Finally, the problem of missing data is discussed in detail.

  • The Continuum Model for Linear Arrays

    This chapter contains sections titled: The Linear Array without External Injection The Linear Array with External Injection Beam‐Steering via End Detuning Beam‐Steering via End Injection Conclusion

  • Three-Phase EPLL-II

    This chapter presents the second member of the three-phase enhanced phase- locked loop (3EPLL) structures. This structure, called the 3EPLL-II, is a direct extension of the 3EPLL-I in order to obviate its major shortcoming with regard to input signal unbalance. The 3EPLL-II inherits all properties of the 3EPLL-I, and in addition to those, it avoids the double-frequency error caused by the negative-sequence component. The 3EPLL-II is comprised of a 3EPLL-I on top and another modified 3EPLL-I on the bottom. The chapter explains the derivation of 3EPLL-II and the modular representation of 3EPLL-II. Representation of the 3EPLL-II in stationary domain is developed and a linear time invariant (LTI) model for the 3EPLL-II is derived for design purposes. The chapter highlights that the performance of the 3EPLL-II is controlled by two gains which makes its design stage very simple.

  • Linear Dynamic Systems

    This chapter discusses the dynamic models used in Kalman filtering, and especially those represented by systems of linear differential equations. It demonstrates, using specific examples, how one goes about building such models and how one can go from a model using differential equations to one suitable for Kalman filtering. The chapter characterizes the measurable outputs of dynamic systems as functions of the internal states and inputs of the system. The treatment is deterministic, in order to define functional relationships between inputs and outputs. Observability is the issue of whether the state of a dynamic system with a known model is uniquely determinable from its inputs and outputs. It is essentially a property of the given system model. A given linear dynamic system model with a given linear input/output model is considered observable if and only if its state is uniquely determinable from the model definition, its inputs, and its outputs.

  • Enhanced Phase-Locked Loop

    This chapter deals with the basic enhanced phase-locked loop (EPLL) structure. The EPLL enhances the standard PLL by removing its main drawback, which is the presence of double-frequency errors. EPLL achieves this task by means of estimating the amplitude of the input signal and using it within a new loop to remove the error. The EPLL provides an estimate of the input signal magnitude and also provides a filtered version of the input signal. It serves as a core and a building block for numerous developments. The chapter focuses on the derivation, principles of operation, linear model, and design guidelines pertaining to the EPLL. The droop control method (DCM) is widely used to control the operation of synchronous generators (SGs) in a power system. Three scenarios are considered to study the dynamic performance of the EPLL: the step jumps in the input signal variables, amplitude modulations, and phase- angle modulations.

  • A Topology-Aware Evolutionary Algorithm for Reverse-Engineering Gene Regulatory Networks

    This chapter is concerned with modeling and simulating the dynamics of gene regulatory networks (GRNs). It explains the process of reverse-engineering GRNs from time-series gene expression data sets. The idea is to discover an optimal set of parameters for a computational model of the network that is able to adequately simulate the behavior described by the gene expression data sets. The chapter investigates three different mathematical methods used in computational models that are based on ordinary differential equations. These methods include Artificial Neural Network (ANN) method, S-System (SS) method and General Rate Law of Transcription (GRLOT) method. The mathematical models investigated in the chapter require a significant number of parameters to be fine-tuned in order for the models to accurately simulate real biological network behavior. In order to take advantage of available computational resources, parallel evolutionary algorithms are implemented using QosCosGrid- OpenMPI (QCG-OMPI). neural nets; reverse engineering

  • INTRODUCTION TO ELECTRICAL ENGINEERING SIMULATION

    Theoretical modeling¿¿¿based analysis is a process where a model is set up based on laws of nature and logic, using mostly mathematics, physics, and engineering¿¿¿ initially with simplified assumptions about their processes and aiming at finding an input/output model. Integrators and function generation can accomplish simulation of an ordinary differential equation (ODE). A state¿¿¿space formulation allows mathematical implementation with ODE solvers that can be computed by MATLAB and supports the definition of a block diagram for signal modeling simulators, such as Simulink. State variables are directly related to the energy storage elements of a system, and the ODEs can be derived from nodal or mesh analysis. ECAP was the first general program for solving time¿¿¿varying circuit equations. Differential equation¿¿¿based systems are developed and simulated from practical examples that focus typical electrical circuit applications, energy conversion, renewable energy sources, interconnection of distributed generation, power electronics, power systems, and power quality problems.

  • Techniques and Research



Standards related to Differential equations

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