... second-order stationaryfield which is a lognormal distribution, with an isotropic exponential correlation ...the algorithms to generate Gaussianrandom ...the algorithms based ...
... order stationaryfield which has a lognormal distribution, with an isotropic exponential covariance ...generate Gaussianrandom fields based on the Circulant Embedding method and its ...
... the Random Function in order to obtain an estimated sample covariance or vari- ogram ...natural field is unrealistic because there are not multiple parallel physical ...a Random Function, obtained as ...
... and Gaussian process modelling have proven efficient in a number of classification and prediction problems, finding a suitable kernel for a given application is often judged ...standard stationary ...
... Fig. 3. Defogging results on synthetic images from FRIDA2 database. First line: the image with homogeneous fog and Gaussian noise. Second line: the obtained restored images using proposed MRF model. Notice how ...
... estimate for both strong and weak error of ...efficient for widely class of spectral density model used in the practice in which the Gaussianrandomfield and its spectral density are ...
... and Gaussian process modelling have proven efficient in a number of classification and prediction problems, finding a suitable kernel for a given application is often judged ...standard stationary ...
... Abstract: Random distortion testing (RDT) [ 1 ] addresses the problem of testing whether or not a random signal, Ξ, deviates by more than a specified tolerance, τ, from a fixed value, ξ 0 ...test for ...
... Empirical random covariance matrices, whose probabilistic study may be traced back to Wishart [ 57 ] in the late twenties, play an important role in applied ...fluctuations for linear spectral statistics of ...
... Sampling; Gaussianrandomfield; unconditionnal simulation ...tools for the modeller: they allow robustness of model predictions to be checked and help identifying the input factors that ...
... inequality for maxima of Gaussianrandom vectors, which is another main result of this paper (see Comment 4 for what anti-concentration inequalities here precisely refer to and how they differ ...
... into stationary domains, thereby increasing the required professional time for modelling and potentially producing disjointed domains that are globally ...
... Uniform randomgeneration, object grammars, ☎ -equations 1 Introduction An object grammar defines classes of objects by means of terminal objects and certain types of operations applied to the ...pictures. ...
... We attempt to overcome the limitations of previ- ous work on the detection of design defects by defining these defects synthetically and by generating detection algorithms automatically. We enhance the specifica- ...
... To prove this theorem, we are going to apply a concentration-compactness lemma that we state below. The reader may refer to [3] and [4] for more details on this kind of approach. The particular shape of the energy ...
... a random number generator which produces sequences from parameters that we cannot ...the random number generator of the Netscape browser used for the Secure Sockets Layer (SSL) ...of random ...
... a randomgeneration task similar to that conducted in Experiment ...a random se- quence, at each of three production rates (4, 2, and 1 ...correlations for five of the six scores were ...
... suitable for predictions if the data is generated by any other ...allowances for additive data cannot depict the complexity of some (more general) ...
... these random streams produced on GP-GPU? And more importantly: how can we ensure that they are independent? These two main problems led us to think about design guidelines that will hopefully help developers to ...