Concept

Low-discrepancy sequence

Related publications (32)

MATHICSE Technical Report : Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a countable sequence of terms in a ...

MATHICSE2015

Discarding low quality Minutia Cylinder-Code pairs for improved fingerprint comparison

Andrzej Drygajlo, Mohammad Hamed Izadi

Local minutiae descriptors such as Minutia Cylinder-Code (MCC) are becoming more popular in modern fingerprint matching systems. The matching performance depends a lot on the fingerprint image quality in global and local levels. Rejecting part of the lowes ...

2015

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Fabio Nobile, Lorenzo Tamellini

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number

N

of random inputs and an analytic dependence of the s ...

2014

MATHICSE Technical Report : Convergence of quasi-optimal stochastic Galerkin methods for a class of PDES with random coefficients

Fabio Nobile, Lorenzo Tamellini

In this work we consider quasi-optimal versions of the Stochastic Galerkin Method for solving linear elliptic PDEs with stochastic coeffcients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solu ...

MATHICSE2012

Compressibility of Deterministic and Random Infinite Sequences

Michaël Unser, Arash Amini

We introduce a definition of the notion of compressibility for infinite deterministic and i.i.d. random sequences which is based on the asymptotic behavior of truncated subsequences. For this purpose, we use asymptotic results regarding the distribution of ...

IEEE2011

Neural Pre-coding Increases the Pattern Retrieval Capacity of Hopﬁeld and Bidirectional Associative Memories

Wulfram Gerstner, Mohammad Amin Shokrollahi, Krishna Kumar, Amir Hesam Salavati

We consider the problem of neural association, which deals with the retrieval of a previously memorized pattern from its noisy version. The performance of various neural networks developed for this task may be judged in terms of their pattern retrieval cap ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Applications of Derandomization Theory in Coding

Mahdi Cheraghchi Bashi Astaneh

Randomized techniques play a fundamental role in theoretical computer science and discrete mathematics, in particular for the design of efficient algorithms and construction of combinatorial objects. The basic goal in derandomization theory is to eliminate ...

EPFL2010

Authentication with built-in encryption by using moire parallax effects between fixed correlated s-random layers

Roger Hersch, Isaac Amidror

This invention discloses new methods and security devices for authenticating documents and valuable products which may be applied to any support, including transparent synthetic materials and traditional opaque materials such as paper. The invention relate ...

2009

Interleaving bisection stimuli - randomly or in sequence - does not disrupt perceptual learning, it just makes it more difficult

Michael Herzog, Carl Kristoffer Aberg

Presenting stimuli of two or more stimulus types randomly interleaved, so called roving, disrupts perceptual learning in many paradigms. Recently, it was shown that no disruption occurs when Gabor stimuli were presented interleaved in sequence, instead of ...

Elsevier2009

Halton Sampling for Image Registration Based on Mutual Information

Michel Bierlaire, Michaël Unser, Philippe Thévenaz

Mutual information is a widely used similarity measure for aligning multimodal medical images. At its core it relies on the computation of a discrete joint histogram, which itself requires image samples for its estimation. In this paper we study the influe ...

Sampling Publishing2008

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Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Fabio Nobile, Lorenzo Tamellini

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number

N

of random inputs and an analytic dependence of the s ...

2014