366 research outputs found
Eigenvector localization for random band matrices with power law band width
It is shown that certain ensembles of random matrices with entries that
vanish outside a band around the diagonal satisfy a localization condition on
the resolvent which guarantees that eigenvectors have strong overlap with a
vanishing fraction of standard basis vectors, provided the band width
raised to a power remains smaller than the matrix size . For a
Gaussian band ensemble, with matrix elements given by i.i.d. centered Gaussians
within a band of width , the estimate holds.Comment: 30 pages; corrected typo
Neuroelectronic Systems: Binding Neurons to Electric Circuits
This paper is devoted to description of a new type of information system based on interaction of biological neurons and electronic components – neuroelectronic (NE) system. Main features and components, like neural network sensor, of NE are briefly put into consideration followed with an example of electric interaction between neural network of a snail Lymnaea Stagnalis neurons and electronic MOSFET sensor
Notes on Stein-Sahi representations and some problems of non harmonic analysis
We discuss one natural class of kernels on pseudo-Riemannian symmetric
spaces.Comment: 40p
About possibility to locate an EQ epicenter using parameters of ELF/ULF preseismic emission
A relation between parameters of preseismic ULF/ELF emissions and EQ is studied. The magnetic data measured at Karymshino station (Kamchatka, Russia) along with data on local seismic activity during eight years of observations (2001–2008) are taken for the analysis. Source azimuth is detected in different techniques, based on the analysis of the total field and its polarized pulsed component. The latter technique shows a better accuracy in the source azimuth detection. The errors of the method are associated with existence of non-seismic sources and with use of one-point observation. The second error can be eliminated by development of multi-point observations
Coherent frequentism
By representing the range of fair betting odds according to a pair of
confidence set estimators, dual probability measures on parameter space called
frequentist posteriors secure the coherence of subjective inference without any
prior distribution. The closure of the set of expected losses corresponding to
the dual frequentist posteriors constrains decisions without arbitrarily
forcing optimization under all circumstances. This decision theory reduces to
those that maximize expected utility when the pair of frequentist posteriors is
induced by an exact or approximate confidence set estimator or when an
automatic reduction rule is applied to the pair. In such cases, the resulting
frequentist posterior is coherent in the sense that, as a probability
distribution of the parameter of interest, it satisfies the axioms of the
decision-theoretic and logic-theoretic systems typically cited in support of
the Bayesian posterior. Unlike the p-value, the confidence level of an interval
hypothesis derived from such a measure is suitable as an estimator of the
indicator of hypothesis truth since it converges in sample-space probability to
1 if the hypothesis is true or to 0 otherwise under general conditions.Comment: The confidence-measure theory of inference and decision is explicitly
extended to vector parameters of interest. The derivation of upper and lower
confidence levels from valid and nonconservative set estimators is formalize
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