Conferences related to Vectors

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2014 IEEE International Symposium on Information Theory (ISIT)

Annual international symposium on processing, transmission, storage, and use of information, as well as theoretical and applied aspects of coding, communications, and communications networks.

  • 2013 IEEE International Symposium on Information Theory (ISIT)

    The conference covers a broad range of topics in information theory including coding theory, communication theory, compression, data security, detection and estimation, information theory and statistics, information theory in networks, multi-terminal information theory, pattern recognition and learning, quantum information theor, sequences and complexity, Shannon theory, signal processing, source coding as well as novel applications of information theory.

  • 2012 IEEE International Symposium on Information Theory - ISIT

    Fundamentals and applications of information theory, coding, communications and networks.

  • 2011 IEEE International Symposium on Information Theory - ISIT

    Information Theory

  • 2010 IEEE International Symposium on Information Theory - ISIT

    The conference deals with fundamental limits in communication at the physical and higher levels.

  • 2009 IEEE International Symposium on Information Theory - ISIT

    Coding theory and pratice, Information theory, Communication theory, Muti-terminal information theory, Shannon theory, Detection and estimation, Sequences and complexity, Source coding, Cryptography and data security, Compression


2013 6th International Symposium on Computational Intelligence and Design (ISCID)

Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models.


2013 9th International Conference on Information, Communications & Signal Processing (ICICS)

The conference provides an opportunity for researchers around the world to exchange ideas and latest research results in areas such as multimedia systems, information systems, signal processing, communications, networking and related fields.


2013 International Carnahan Conference on Security Technology (ICCST)

This international conference is a forum for all aspects of physical, cyber and electronic security research, development, systems engineering, testing, evaluation, operations and sustainability. The ICCST facilitates the exchange of ideas and information.

  • 2012 IEEE International Carnahan Conference on Security Technology (ICCST)

    Research, development, and user aspects of security technology, including principles of operation, applications, and user experiences.

  • 2011 International Carnahan Conference on Security Technology (ICCST)

    This annual conference is the world s longest -running, international technical symposium on security technology. This conference is a forum for collaboration on all aspects of physical, cyber and electronic security research, development, systems engineering, testing, evaluation, operations and sustainment. The ICCST facilitates the exchange of ideas and sharing of information on both new and existing technology and systems. Conference participants are encouraged to consider the impact of their work on society. The ICCST provides a foundation for support to authorities and agencies responsible for security, safety and law enforcement in the use of available and future technology.

  • 2010 IEEE International Carnahan Conference on Security Technology (ICCST)

    The ICCST is a forum for researchers and practitioners in both new and existing security technology, providing an interchange of knowledge through paper presentations and publication of proceedings that have been selected by the ICCST organizing committee.


2012 8th International Conference on Natural Computation (ICNC)

ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering and more.

  • 2011 Seventh International Conference on Natural Computation (ICNC)

    ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering, and more.

  • 2010 Sixth International Conference on Natural Computation (ICNC)

    ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering, and more.


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Periodicals related to Vectors

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Control Systems Magazine, IEEE

The magazine covers theory, analysis, design (computer-aided design), and practical implementation of circuits, and the application of circuit theoretic techniques to systems and to signal processing. Content is written for the spectrum of activities from basic scientific theory to industrial applications.


Information Theory, IEEE Transactions on

The fundamental nature of the communication process; storage, transmission and utilization of information; coding and decoding of digital and analog communication transmissions; study of random interference and information-bearing signals; and the development of information-theoretic techniques in diverse areas, including data communication and recording systems, communication networks, cryptography, detection systems, pattern recognition, learning, and automata.


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.



Most published Xplore authors for Vectors

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Xplore Articles related to Vectors

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On a state feedback anisotropy-based control problem for linear discrete-time descriptor systems

Olga G. Andrianova Proceedings of the 2014 15th International Carpathian Control Conference (ICCC), 2014

This paper deals with a suboptimal state feedback anisotropy-based control problem for linear time-invariant discrete-time descriptor systems. The goal is to design a state feedback for the system such that the closed-loop system is admissible, and its anisotropic norm (mean anisotropy level is set) is bounded by a given positive real value.


A Novel Image Encryption Algorithm Based on Hyperchaotic System and Shuffling Scheme

Xiaoheng Deng; Chunlong Liao; Congxu Zhu; Zhigang Chen 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

We propose an improved image encryption algorithm based on hyper chaotic system and permutation-diffusion structure. In the permutation process, the algorithm introduces plain-text feedback mechanism that makes the permutation effect not only associated with the chaotic sequences, but also related to plain-text. And in the diffusion process, the algorithm introduces both cipher-text and plain-text feedback mechanisms to diffuse the permuted ...


Nonlinear blind source separation based on radial basis function

Ding Liu; Yan Zhao Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788), 2004

Radial basis function (RBF) neural network is used as a de-mixing system for nonlinear blind source separation (BSS). The nonlinear mixing mapping is assumed to exist and able to be approximated using RBF network. The object criterion is based on the maximum entropy (ME) approach. To ensure the entropy of the outputs has upper bounded, a special sigmoid function is ...


Receiver-Based Flow Control for Networks in Overload

Chih-ping Li; Eytan Modiano IEEE/ACM Transactions on Networking, 2015

We consider utility maximization in networks where the sources do not employ flow control and may consequently overload the network. In the absence of flow control at the sources, some packets will inevitably have to be dropped when the network is in overload. To that end, we first develop a distributed, threshold-based packet-dropping policy that maximizes the weighted sum throughput. ...


A New Camera Calibration Based on Neural Network with Tunable Activation Function in Intelligent Space

Mingxin Yuan; Haixiu Hu; Yafeng Jiang; Sheng Hang 2013 Sixth International Symposium on Computational Intelligence and Design, 2013

In order to solve the camera calibration in intelligent space of mobile robot, a new calibration method based on neural network with tunable activation function (TAF) is presented. In the TAF model, the inner product mode is adopted in the calculation of output signal in synapse model and the S function is adopted in base function. Taking the coordinate in ...


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Educational Resources on Vectors

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eLearning

On a state feedback anisotropy-based control problem for linear discrete-time descriptor systems

Olga G. Andrianova Proceedings of the 2014 15th International Carpathian Control Conference (ICCC), 2014

This paper deals with a suboptimal state feedback anisotropy-based control problem for linear time-invariant discrete-time descriptor systems. The goal is to design a state feedback for the system such that the closed-loop system is admissible, and its anisotropic norm (mean anisotropy level is set) is bounded by a given positive real value.


A Novel Image Encryption Algorithm Based on Hyperchaotic System and Shuffling Scheme

Xiaoheng Deng; Chunlong Liao; Congxu Zhu; Zhigang Chen 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

We propose an improved image encryption algorithm based on hyper chaotic system and permutation-diffusion structure. In the permutation process, the algorithm introduces plain-text feedback mechanism that makes the permutation effect not only associated with the chaotic sequences, but also related to plain-text. And in the diffusion process, the algorithm introduces both cipher-text and plain-text feedback mechanisms to diffuse the permuted ...


Nonlinear blind source separation based on radial basis function

Ding Liu; Yan Zhao Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788), 2004

Radial basis function (RBF) neural network is used as a de-mixing system for nonlinear blind source separation (BSS). The nonlinear mixing mapping is assumed to exist and able to be approximated using RBF network. The object criterion is based on the maximum entropy (ME) approach. To ensure the entropy of the outputs has upper bounded, a special sigmoid function is ...


Receiver-Based Flow Control for Networks in Overload

Chih-ping Li; Eytan Modiano IEEE/ACM Transactions on Networking, 2015

We consider utility maximization in networks where the sources do not employ flow control and may consequently overload the network. In the absence of flow control at the sources, some packets will inevitably have to be dropped when the network is in overload. To that end, we first develop a distributed, threshold-based packet-dropping policy that maximizes the weighted sum throughput. ...


A New Camera Calibration Based on Neural Network with Tunable Activation Function in Intelligent Space

Mingxin Yuan; Haixiu Hu; Yafeng Jiang; Sheng Hang 2013 Sixth International Symposium on Computational Intelligence and Design, 2013

In order to solve the camera calibration in intelligent space of mobile robot, a new calibration method based on neural network with tunable activation function (TAF) is presented. In the TAF model, the inner product mode is adopted in the calculation of output signal in synapse model and the S function is adopted in base function. Taking the coordinate in ...


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IEEE-USA E-Books

  • A Fast and Practical Algorithm for Generalized Penetration Depth Computation

    We present an efficient algorithm to compute the generalized penetration depth (PDg) between rigid models. Given two overlapping objects, our algorithm attempts to compute the minimal translational and rotational motion that separates the two objects. We formulate the PDg computation based on modeldependent distance metrics using displacement vectors. As a result, our formulation is independent of the choice of inertial and body-fixed reference frames, as well as specific representation of the configuration space. Furthermore, we show that the optimum answer lies on the boundary of the contact space and pose the computation as a constrained optimization problem. We use global approaches to find an initial guess and present efficient techniques to compute a local approximation of the contact space for iterative refinement. We highlight the performance of our algorithm on many complex models.

  • Basic Electromagnetics

    This chapter contains sections titled: Vectors Ampere's Law Magnetic Materials Faraday's Law Potentials Maxwell's Equations Problems References

  • Tensor Analysis

    This chapter contains sections titled: Contravariant and Covariant Vectors Tensors The Metric Tensor Tensor Properties

  • Intermezzo 5: The Cost of Computing and Vectors

    This chapter contains sections titled: Concrete Time, Abstract Time, The Definition of "on the Order of", A First Look at Vectors

  • Changong Structures, Vectors, and Objects

    This chapter contains sections titled: More Practice with Vectors, Collections of Structures with Cycles, Backtracking with State

  • Malware Detection System Using Affinity Vectors

    This chapter proposes an immune-based virus detection system using affinity vectors (IVDS) based on the negative selection and clonal selection algorithms in artificial immune system (AIS). AVDS first generates the detector set from virus files in dataset, negative selection is used to eliminate autoimmunity detectors for the detector set, while clonal selection is exploited to increase the diversity of the detector set in the non-self space. The affinity vectors of the training set and the testing set are used to train and test classifiers, respectively. Finally, based on the affinity vectors, three classic classifiers, that is, Support Vector Machine (SVM), radial basis kernel function (RBF) network and k-nearest neighbor (KNN), are used to verify the performance of the model. Experimental results showed that the IVDS with the rbf-SVM classifier has a strong generalization ability with a low false positive rate in detecting unknown viruses.

  • Matlab and Simulink Basics

    This chapter deals with the operations of different variable types such as scalar variables, complex numbers, vectors and matrices. It also deals with the plotting commands that are frequently used. In the symbolic math in MATLAB, the characters (or words) such as a, b, and temp are treated as symbolic variables, not numeric variables. Mathematical expressions can be computed or manipulated in symbolic forms. The commands and functions are all executable directly in the command window. Using a script file, which is also called an m-file in the earlier versions of MATLAB, users can execute various algorithms or can implement user-defined functions. Similar to many other programming languages, MATLAB also supports the use of user-defined functions to avoid repeatedly editing the main body of a code. The subsystem can be saved as a user-defined block to enrich the library Simulink.

  • Fundamentals of Matrix Algebra

    This chapter contains sections titled: Scalars, Vectors, and Matrices Operations on Matrices Linear Dependence and Independence Vector Spaces Linear Transformations Eigenvalues and Eigenvectors Linear Equations Vector and Matrix Norms Condition Number Solved Problems Conclusions Exercise Problems

  • The Unitary Formalism

    This chapter contains sections titled: Unpacking Pauli Quaternions, Pauli Matrices, The Basis Vectors and the Hilbert Space, The Superstition of Superposition, Probability Amplitudes, Spinors, Operators and Operands, Properties of the Density Operator, Schrodinger Equation, Single Qubit Gates, Taking Qubits for a Ride

  • Support Vector Machines on a Budget

    The standard Support Vector Machine formulation does not provide its user with the ability to explicitly control the number of support vectors used to define the generated classifier. We present a modified version of SVM that allows the user to set a budget parameter B and focuses on minimizing the loss attained by the B worst-classified examples while ignoring the remaining examples. This idea can be used to derive sparse versions of both L1-SVM and L2-SVM. Technically, we obtain these new SVM variants by replacing the 1-norm in the standard SVM formulation with various interpolation-norms. We also adapt the SMO optimization algorithm to our setting and report on some preliminary experimental results.



Standards related to Vectors

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No standards are currently tagged "Vectors"