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In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device
Advanced Functional Materials, EarlyView.In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang +19 more
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Infinite Dimensional Analysis, Quantum Probability and Related Topics, 1998
There is a famous formula called Lévy's stochastic infinitesimal equation for a stochastic process X(t) expressed in the form [Formula: see text] We propose a generalization of this equation for a random field X(C) indexed by a contour C. Assume that the X(C) is homogeneous in a white noise x, say of degree n, we can then appeal to the classical ...
Hida, Takeyuki, Si, Si
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There is a famous formula called Lévy's stochastic infinitesimal equation for a stochastic process X(t) expressed in the form [Formula: see text] We propose a generalization of this equation for a random field X(C) indexed by a contour C. Assume that the X(C) is homogeneous in a white noise x, say of degree n, we can then appeal to the classical ...
Hida, Takeyuki, Si, Si
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Markov random fields and gibbs random fields
Israel Journal of Mathematics, 1973Spitzer has shown that every Markov random field (MRF) is a Gibbs random field (GRF) and vice versa when (i) both are translation invariant, (ii) the MRF is of first order, and (iii) the GRF is defined by a binary, nearest neighbor potential. In both cases, the field (iv) is defined onZ v, and (v) at anyxeZv, takes on one of two states.
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Hidden Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007We present a discriminative latent variable model for classification problems in structured domains where inputs can be represented by a graph of local observations. A hidden-state Conditional Random Field framework learns a set of latent variables conditioned on local features. Observations need not be independent and may overlap in space and time.
Ariadna, Quattoni +4 more
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Invariant random boolean fields
Mathematical Notes of the Academy of Sciences of the USSR, 1969In the set of finite binary sequences a Markov process is defined with discrete time in which each symbol of the binary sequence at time t+1 depends on the two neighboring symbols at time t. A proof is given of the existence and uniqueness of an invariant distribution, and its derivation is also given in a number of cases.
Belyaev, Yu. K. +2 more
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Structures in random fields: Gaussian fields
Physical Review A, 1992We present two alternative methods for evaluating the probability densities of structures defined by d degrees of freedom in random fields. For Gaussian random fields, both differentiable and nondifferentiable, the application of these methods is considered in detail.
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Advances in Applied Probability, 1978
is of great importance in many applications. For example, if we consider a geographical map and denote height by X(t) where t is the set of geographical coordinates, Z(S) is the height of the highest mountain in the area S. In general, it is not possible to make any exact useful statements about the distribution of Z(S), and one must have recourse to ...
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is of great importance in many applications. For example, if we consider a geographical map and denote height by X(t) where t is the set of geographical coordinates, Z(S) is the height of the highest mountain in the area S. In general, it is not possible to make any exact useful statements about the distribution of Z(S), and one must have recourse to ...
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2008 International Machine Vision and Image Processing Conference, 2008
In this talk the author will outline some of the recent work undertaken by the Oxford Brookes Vision Group, a common theme underlying much of the research is to cast vision problems in terms of combinatorial optimization which provides a rich a deep theory for understanding them, with many new and exciting results.
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In this talk the author will outline some of the recent work undertaken by the Oxford Brookes Vision Group, a common theme underlying much of the research is to cast vision problems in terms of combinatorial optimization which provides a rich a deep theory for understanding them, with many new and exciting results.
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Random fields on random graphs
Advances in Applied Probability, 1992The distribution (1) used previously by the author to represent polymerisation of several types of unit also prescribes quite general statistics for a random field on a random graph. One has the integral expression (3) for its partition function, but the multiple complex form of the integral makes the nature of the expected saddlepoint evaluation in ...
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