The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus
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We address adaptive multivariate polynomial approximation by means of the discrete least-squares method with random evaluations, to approximate in the L2 probability sense a smooth function depending on a random variable distributed according to a given pr ...
Consider a finite set of sources, each producing independent identically distributed observations that follow a unique probability distribution on a finite alphabet. We study the problem of matching a finite set of observed sequences to the set of sources ...
Institute of Electrical and Electronics Engineers2015
We study the nonlinear stochastic heat equation in the spatial domain R, driven by space-time white noise. A central special case is the parabolic Anderson model. The initial condition is taken to be a measure on R, such as the Dirac delta function, but th ...
An optical rangefinder based on time-of-flight measurement, radiates pulsed light toward an object (70), and receives reflected light from the object, the receiver operating in a photon counting mode, so as to generate a pulse for a detected photon. There ...
A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (p ...
This paper provides an original framework for the fatigue reliability analysis of a road bridge; the framework is applied to the Venoge bridge, a composite steel concrete bridge within the A1 Swiss highway. Two critical details are selected by inspection: ...
We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands are strongly correlated and subject to fashion trends that are not fully understood at the time when orders are placed. The demand distribution is known to be ...
We analyze the stability and accuracy of discrete least squares on multivariate poly- nomial spaces to approximate a given function depending on a multivariate random variable uniformly distributed on a hypercube. The polynomial approximation is calculated ...
We analyze the stability and accuracy of discrete least squares on multivariate polynomial spaces to approximate a given function depending on a multivariate random variable uniformly distributed on a hypercube. The polynomial approximation is calculated s ...
We present new counterexamples, which provide stronger limitations to sums-differences statements than were previously known. The main idea to improve over the original counterexamples by Ruzsa is to consider non-uniform probability measures. ...