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.


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 ...




Xplore Articles related to Higher order statistics

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An emerging alliance: higher order statistics should partner conventional statistics in digital signal processing applications

Chambers, J.; Stathaki, T. Higher Order Statistics in Signal Processing: Are They of Any Use? IEE Colloquium on, 1995

The conjecture of the paper is that higher order statistics are best used in combination with conventional second order statistics; not in isolation. This is demonstrated by showing some established and new examples where this proposal has been utilised. A conventional, second order, spectral estimator stabilises the statistical performance of higher order spectral estimation techniques. The performance of an adaptation ...


Novel asymptotic results on the high-order statistics of the channel capacity over generalized fading channels

Yilmaz, F.; Alouini, M.-S. Signal Processing Advances in Wireless Communications (SPAWC), 2012 IEEE 13th International Workshop on, 2012

The exact analysis of the higher-order statistics of the channel capacity (i.e., higher-order ergodic capacity) often leads to complicated expressions involving advanced special functions. In this paper, we provide a generic framework for the computation of the higher-order statistics of the channel capacity over generalized fading channels. As such, this novel framework for the higher-order statistics results in simple, closed-form ...


Azimuthal harmonic coefficients of the microwave backscattering from a non-Gaussian ocean surface with the first-order SSA model

Bourlier, C. Geoscience and Remote Sensing, IEEE Transactions on, 2004

In this paper, the first-order small slope approximation is applied to a rough sea surface with non-Gaussian statistics, for which the third- and the fourth- order statistics are taken into account in the calculation of the radar cross section. From the Cox and Munk slope distribution, the higher order statistic moments are derived, and behaviors of the corresponding correlation functions ...


Higher order statistics applied to image segmentation

Harrabi, R.; Sayadi, M.; Fnaiech, F. Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE, 2009

Recent research has shown that image segmentation, has a great importance in many areas and especially in the industrial application, such as robot animation, mobile localization, etc...¶ Also, in medical imaging, it is used for tumor detection and in radar imaging, it is used for target detection. This paper deals with the problem of texture segmentation using higher order statistics. ...


Complex ambiguity functions using nonstationary higher order cumulant estimates

Dae C.Shin; Nikias, C.L. Signal Processing, IEEE Transactions on, 1995

The complex ambiguity function based on second-order statistics (CAF-SOS) has been used to simultaneously estimate the frequency-delay of arrival (FDOA) and time-delay of arrival (TDOA) between two signal measurements; its performance, however, is sensitive to the correlation between two additive noise sources. When the noise sources are assumed to be Gaussian, we develop a new complex ambiguity function based on ...


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Educational Resources on Higher order statistics

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eLearning

Information Theoretic Learning

Principe, Jose Information Theoretic Learning, 2006

This course examines Information Theory and our efforts to develop an information-theoretic criterion which can be utilized in adaptive filtering and neurocomputing. The main aim of our research is to develop new signal processing techniques by going beyond the basic assumptions of Linearity, Gaussianity and Stationarity. By capturing higher order statistics of data using Information Theory, we solve a variety ...


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