Conferences related to Higher order statistics

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IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

Applications of power electronics, artificial intelligence, robotics, and nanotechnology in electrification of automotive, military, biomedical, and utility industries.

  • IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

    Industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.

  • IECON 2012 - 38th Annual Conference of IEEE Industrial Electronics

    The conference will be focusing on industrial and manufacturing theory and applications of electronics,power, sustainable development, controls, communications, instrumentation and computational intelligence.

  • IECON 2011 - 37th Annual Conference of IEEE Industrial Electronics

    industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies.

  • IECON 2010 - 36th Annual Conference of IEEE Industrial Electronics

    IECON is an international conference on industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies. The objectives of the conference are to provide high quality research and professional interactions for the advancement of science, technology, and fellowship.

  • IECON 2009 - 35th Annual Conference of IEEE Industrial Electronics

    Applications of electronics, instrumentation, control and computational intelligence to industrial and manufacturing systems and process. Major themes include power electronics, drives, sensors, actuators, signal processing, motion control, robotics, mechatronics, factory and building automation, and informatics. Emerging technologies and applications such as renewable energy, electronics reuse, and education.


2012 Australian Communications Theory Workshop (AusCTW)

- Coded modulation - Coding theory and practice - Communication systems - Channel characteristics and modeling - Detection and estimation - OFDM and DMT processing techniques - Utra-wide band communications - DSP for communications - Information theory and statistics - Iterative decoding algorithms - Multiuser detection - Cross-layer PHY-MAC-NET arrangements - Fourth generation cellular systems - Blind signal separation techniques



Periodicals related to Higher order statistics

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Geoscience and Remote Sensing, IEEE Transactions on

Theory, concepts, and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.


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 Letters, IEEE

Rapid dissemination of new results in signal processing world-wide.


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.


Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Applications, review, and tutorial papers within the scope of the Systems, Man and Cybernetics Society. Currently, this covers: (1) Integration of the theories of communication, control cybernetics, stochastics, optimization and system structure towards the formulation of a general theory of systems; (2) Development of systems engineering technology including problem definition methods, modeling, and stimulation, methods of systems experimentation, human factors ...



Most published Xplore authors for Higher order statistics

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Xplore Articles related to Higher order statistics

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Detection of Glottal Activity Using Different Attributes of Source Information

Nagaraj Adiga; S. R. M. Prasanna IEEE Signal Processing Letters, 2015

The major activity during speech production is glottal activity and is earlier detected using strength of excitation (SoE). This work uses the normalized autocorrelation peak strength (NAPS) and higher order statistics (HOS) as additional features for detecting glottal activity. The three features, namely, SoE, NAPS, and HOS, are, respectively indicators of different attributes of glottal activity, namely, energy, periodicity, and ...


Analysis of the SAR imaging process of the ocean surface using Volterra models

J. -M. Le Caillec; R. Garello; B. Chapron IEEE Journal of Oceanic Engineering, 2002

The synthetic aperture radar (SAR) process of the ocean surface mapping is studied using a decomposition based on a Volterra model. By a mathematical expansion of the complex exponential of the complete SAR transform, these models decompose the nonlinear distortion mechanisms of the SAR spectrum over different spectra of polynomial interactions. Thus, they offer an alternative modeling (to the exact ...


Sea ice classification using SAR backscatter statistics

J. A. Nystuen; F. W. Garcia IEEE Transactions on Geoscience and Remote Sensing, 1992

Sea ice classification accuracy using standard statistics and higher order texture statistics generated from grey-level co-occurrence (GLC) matrices were compared for synthetic aperture radar (SAR) data collected during the Marginal Ice Zone Experiment (MIZEX) in April 1987. Standard stepwise discriminate analysis was used to identify the statistics modes useful for discrimination. Range was the most effective statistic, correctly classifying the ...


Various type digital filters for an arbitrary sound environmental system with quantized observation mechanism and its application

E. Uchino; M. Ohta; K. Hatakeyama Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on, 1991

The authors describe various state estimation methods of a quantized sound environmental system. The elimination of not only the usual background noise but also the quantization noise owing to digital observation is discussed. The methods include the traditional Kalman filter as a special case when Gaussian distribution is employed and where there is no level quantization. The level quantization mechanism ...


The accuracy of Gilbert models in predicting packet-loss statistics for a single-multiplexer network model

X. Yu; J. W. Modestino; X. Tian Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 2005

The Gilbert model (1-st order Markov chain model) and the single-multiplexer model are two frequently used models in the study of packet-loss processes in communication networks. In this paper we investigate the accuracy of the Gilbert model, and higher-order Markov chain extended Gilbert models, in characterizing the packet-loss process associated with a transport network modeled in terms of a single-multiplexer. ...


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Educational Resources on Higher order statistics

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eLearning

Detection of Glottal Activity Using Different Attributes of Source Information

Nagaraj Adiga; S. R. M. Prasanna IEEE Signal Processing Letters, 2015

The major activity during speech production is glottal activity and is earlier detected using strength of excitation (SoE). This work uses the normalized autocorrelation peak strength (NAPS) and higher order statistics (HOS) as additional features for detecting glottal activity. The three features, namely, SoE, NAPS, and HOS, are, respectively indicators of different attributes of glottal activity, namely, energy, periodicity, and ...


Analysis of the SAR imaging process of the ocean surface using Volterra models

J. -M. Le Caillec; R. Garello; B. Chapron IEEE Journal of Oceanic Engineering, 2002

The synthetic aperture radar (SAR) process of the ocean surface mapping is studied using a decomposition based on a Volterra model. By a mathematical expansion of the complex exponential of the complete SAR transform, these models decompose the nonlinear distortion mechanisms of the SAR spectrum over different spectra of polynomial interactions. Thus, they offer an alternative modeling (to the exact ...


Sea ice classification using SAR backscatter statistics

J. A. Nystuen; F. W. Garcia IEEE Transactions on Geoscience and Remote Sensing, 1992

Sea ice classification accuracy using standard statistics and higher order texture statistics generated from grey-level co-occurrence (GLC) matrices were compared for synthetic aperture radar (SAR) data collected during the Marginal Ice Zone Experiment (MIZEX) in April 1987. Standard stepwise discriminate analysis was used to identify the statistics modes useful for discrimination. Range was the most effective statistic, correctly classifying the ...


Various type digital filters for an arbitrary sound environmental system with quantized observation mechanism and its application

E. Uchino; M. Ohta; K. Hatakeyama Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on, 1991

The authors describe various state estimation methods of a quantized sound environmental system. The elimination of not only the usual background noise but also the quantization noise owing to digital observation is discussed. The methods include the traditional Kalman filter as a special case when Gaussian distribution is employed and where there is no level quantization. The level quantization mechanism ...


The accuracy of Gilbert models in predicting packet-loss statistics for a single-multiplexer network model

X. Yu; J. W. Modestino; X. Tian Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 2005

The Gilbert model (1-st order Markov chain model) and the single-multiplexer model are two frequently used models in the study of packet-loss processes in communication networks. In this paper we investigate the accuracy of the Gilbert model, and higher-order Markov chain extended Gilbert models, in characterizing the packet-loss process associated with a transport network modeled in terms of a single-multiplexer. ...


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IEEE-USA E-Books

  • Higher Order Spectra

    This chapter contains sections titled: Introduction Higher Order Statistics: Definition and Main Properties Bispectrum and Bicoherence: Definitions, Properties, and Estimation Methods Analysis of Nonlinear Signals: Quadratic Phase Coupling Identification of Linear Systems Interaction Among Cardiorespiratory Signals Clinical Applications of HOS: Bispectral Index for Assessment of Anaesthesia Depth

  • Equalizers

    This chapter discusses equalizers for single-carrier transmission in wireless systems. We first set up a time-discrete model for the channel, filters, and equalizer. A noise-whitening filter or precursor equalizer ensures white noise at the equalizer input. Transmit filter, channel, matched filter, and noise whitening filter can be modeled together by an equivalent time-discrete channel. We then turn to the various types of equalizers. Linear equalizers consist of linear filters, usually tapped delay lines (though IIR filters and lattice filters are also possible), whose coefficients are optimized according to certain criteria. Zero-forcing equalizers eliminate intersymbol interference, but lead to noise enhancement, while minimum mean square error (MMSE) equalizers trade off these error sources. Adaptation algorithms for the coefficients trade off complexity, convergence rate, and misadjustment. Example algorithms include the least mean square (LMS) algorithm (stochastic gradient method), the recursive least squares algorithm (RLS), or direct computation of the Wiener filter. Decision feedback equalizer (DFE) consist of a feedforward filters and a feedback filter that eliminates the postcursor impact. DFEs generally perform well, but must avoid error propagation. The best performance is obtained by maximum-likelihood sequence estimators (MLSE) or Viterbi equalizers. They act similar to Viterbi decoders for convolutional codes, since the channel can be interpreted as a rate-1 convolutional encoder. Finally, we discuss blind equalizers, which do not require a training sequence for detection. Certain signal properties, e.g., constant envelope, finite symbol alphabet, cyclostationarity, or spectral correlation, can be used to separate the effect of the channel on the received signal from the signal modulation, and perform implicit equalization. The best-known algorithms are the constant-modulus algorithm (CMA), blind MLSE, and algorithms using higher- order statistics.



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