Results 161 to 170 of about 17,823 (205)

Partition Function Zeros of the Frustrated J₁-J₂ Ising Model on the Honeycomb Lattice. [PDF]

Entropy (Basel)
Gessert D, Weigel M, Janke W.
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Measuring Statistical Dependence via Characteristic Function IPM. [PDF]

Entropy (Basel)
Daniušis P, Juneja S, Kuzma L, Marcinkevičius V.   +3 more
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CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning. [PDF]

Sensors (Basel)
Wu T, Zhu Q, Mao R, Hu C, Wei S.
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A Novel Version of the Arcsine-Rayleigh Distribution with Entropy Measures, Statistical Inference, and Applications. [PDF]

Entropy (Basel)
Al-Moisheer AS, Sultan KS, Mousa MN, Mansour MMM.   +3 more
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Mimicking classical noise in ion channels by quantum decoherence. [PDF]

Sci Rep
Seifi M, Soltanmanesh A, Shafiee A.
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An architecture for the estimation of higher order cumulants

IEEE International Conference on Acoustics Speech and Signal Processing, 1993
To achieve real-time performance in signal processing applications that require the estimation of higher order statistics, it is necessary to introduce parallel processing and pipelining. The authors present a two stage VLSI architecture for the computation of all the non-negative lags of the cumulants of a real, one-dimensional data sequence.
Haris M. Stellakis, Elias S. Manolakos
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Blind estimation using higher-order cumulants

Proceedings of ISCAS'95 - International Symposium on Circuits and Systems, 2002
This paper presents a higher-order cumulant based blind estimation algorithm for estimating the channel matrix in a n-sensor-m-source system under a noisy environment. The output from an array of n spatially separated sensors is the only available information that can be used to derive the channel parameters. The algorithm requires neither the additive
W. K. Lai, P. C. Ching
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Higher-order Multi-cumulant Factor Analysis

SSRN Electronic Journal, 2021
We estimate the latent factors driving the non-normal dependence in high dimensional panel data using Higher-order multi-cumulant Factor Analysis (HFA). This new approach consists of an eigenvalue ratio test to select the number of non-Gaussian factors, and uses alternating regressions to estimate both the Gaussian and non-Gaussian factors.
Wanbo Lu, Guanglin Huang, Kris Boudt
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Cumulative Higher-Order Logic as a Foundation for Set Theory

MLQ, 2000
The authors study systems \(K(\alpha)\) of transfinite cumulative types, where the types consist of ordinals less than \(\alpha\) and there is an implicit comprehension principle (because of the presence of lambda terms). (My notation here and below differs inessentially from the authors.) Let \(K\# (\alpha)\) denote the corresponding non-cumulative ...
Wolfgang Degen, Jan Johannsen
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A bibliography of higher-order spectra and cumulants

IEEE Signal Processing Magazine, 1994
The interest in higher-order spectra and cumulants was renewed in the early 1980s due, in part, to the need to solve detection, estimation, and identification problems when the interfering noise source was non-Gaussian. The bibliography is a list of refereed journal papers.
P.A. Delaney, D.O. Walsh
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