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Higher order statistics of antenna subset diversity
IEEE Transactions on Wireless Communications, 2003We use a virtual-branch technique to derive higher order statistics of the output signal-to-noise ratio (SNR) of antenna subset diversity in a multipath fading environment. In particular, closed-form expressions of the cumulants, central moments, skewness, and kurtosis for various antenna subset diversity schemes are derived.
Moe Z. Win +2 more
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2020
Higher order statistics (HOS) are meant for nonlinear signal processing, dealing with signals from nonlinear systems. They are used to extract information from random signals. Second order statistics like autocorrelation function and probability density function are used only for linear signals such as Gaussian noise. Nonlinear signal processing can be
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Higher order statistics (HOS) are meant for nonlinear signal processing, dealing with signals from nonlinear systems. They are used to extract information from random signals. Second order statistics like autocorrelation function and probability density function are used only for linear signals such as Gaussian noise. Nonlinear signal processing can be
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Arrhythmia classification using higher order statistics
2008 IEEE 16th Signal Processing, Communication and Applications Conference, 2008In this work, the features are extracted for the arrhythmia classification from the electrocardiograph (ECG) signals by using Higher order statistics. K-nearest neighborhood algorithm is used as classifier. Cumulants are calculated from the raw signals obtained from consecutive sample values of each R peak in ECG signals and used as features.
Kutlu, Yakup +2 more
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Higher Order Statistics for Composite Fading Models
IEEE Wireless Communications Letters, 2019This letter presents a novel, general second-order statistics framework for composite fading models. The aim is to obtain expressions for the level crossing rate and average fade duration statistics in any fading scenario. Two formulations are presented: 1) one that leads to exact expressions and 2) another that leads to approximate ones.
Rafael Augusto Pedriali +2 more
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Higher Order Statistics As An Aid In Campimetric Diagnosis
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991, 2005An automatic campimeter, using a pC provided with standard peripherals, has been set-up at the V Clinica Neurologica of the Umberto I° Hospital of Rome. Parameters usefull to detect specific pathologies have been automatically extracted. These features have been examined by means of univariate and multivariate statistical tools.
FILLIGOI, Giancarlo +3 more
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Higher Order Statistical Analysis of Fluctuations in a Plasma
Physica Scripta, 2003Summary: Turbulent fluctuations are a common phenomena in most plasma systems. Most of the analysis is done by conventional Fourier techniques that extract information only in the frequency domain with temporal information usually missing. Also nonlinear interaction between different modes cannot be identified.
Narayanan, Ramesh +2 more
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On interference detection using higher-order statistics
2015 IEEE 13th International Conference on Industrial Informatics (INDIN), 2015In applications with strict requirements regarding reliability and real time capability such as factory and process automation, it is critical to detect sources of interference that might corrupt data packets leading to retransmissions and delays. To tackle this issue we propose a method for measuring and quantifying radio interference using higher ...
Ahmad Saad, Barbara Staehle, Yun Chen
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Higher order statistical analysis of Turkish phones
2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014In this study, histograms of Turkish phones were examined using higher order cumulants. As is known, phones constituting a language, are composed of letters as vowels and consonants. These letters can also be grouped as voiced and unvoiced phones. It is observed that unvoiced letters show a Gaussian-like distribution and result in small values of ...
Hakan Tora, Baran Uslu
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2002
Purpose In this chapter, we present a few basic notions about higher order statistics that generalise notions defined above for second order statistics. We show, in particular, how the definition of the spectral representation of a process can be generalised for processes that are stationary at orders higher than two.
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Purpose In this chapter, we present a few basic notions about higher order statistics that generalise notions defined above for second order statistics. We show, in particular, how the definition of the spectral representation of a process can be generalised for processes that are stationary at orders higher than two.
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Higher-Order and Cyclostationary Statistics
1999Until the mid-1980’s, signal processing — signal analysis, system identification, signal estimation problems, etc. — was primarily based on second-order statistical information. Autocorrelations and cross-correlations are examples of second-order statistics (SOS). The power spectrum which is widely used and contains useful information is again based on
A. McCormick, A. K. Nandi
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