This paper presents a new mutation strategy for the Metropolis light transport algorithm, which works in the unit cube of pseudo-random numbers instead of mutating in the path space. This transformation makes the integrand have lower variation and thus increases the acceptance probability of the mutated samples. Higher acceptance ratio, in turn, reduces the correlation of the samples, which inc...

Abstract: The paper presents a study of properties of ensemble averages of Wigner time-frequency distributions (WDs) of random processes defined by statistically independent samples of stationary and nonstationary Gaussian noise and of radio-frequency telecommunication signals. We used samples of PSK and FSK signals transmitting random telegraph signals. The WDs of single samples of these rando...

For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples from these distributions. The primary drawback to traditional Markov chain methods is that the mixing time of the chain is usually unknown, which makes it impossible to determine how close the output samples are to having t...

STUDY OBJECTIVE We evaluate the ability of 4 sampling methods to generate representative samples of the emergency department (ED) population. METHODS We analyzed the electronic records of 21,662 consecutive patient visits at an urban, academic ED. From this population, we simulated different models of study recruitment in the ED by using 2 sample sizes (n=200 and n=400) and 4 sampling methods...

Absract: The Sampling-Reconstruction Procedure (SRP) of random process and field realizations is a very popular problem during a lot of decades. Unfortunately, this problem is completely not solved until present time. There is a well-known Balakrishnan ́s theorem. This theorem describes SRP of stationary random process realizations. This theorem is characterized by some principal drawbacks: the ...

Estimation of function expectation θ = Ef(X1, X2, ..., Xm) is considered. For independent variables X1, X2, ..., Xm, sample populations H1, H2, ...,Hm are available as the primary data. The resampling approach uses the usual simulation procedure. For that, the random variables {Xi} are not generated by random number generators in accordance with the estimated probabilistic distributions, but ar...

We reconstruct the temporal response of a random medium by using speckle intensity frequency correlations. When the scattered field from a random medium is described by circular complex Gaussian statistics, we show that third-order correlations permit retrieval of the Fourier phase of the temporal response with bispectral techniques. Our experimental results for random media samples in the diff...

We consider the problem of inferring the underlying graph using samples from a Markov random field defined on the graph. In particular, we consider the special but interesting case when the underlying graph comes from a distribution on sparse graphs. We provide matching upper and lower bounds for the sample-complexity of learning the underlying graph of a hard-core model, when the underlying gr...

Many Random Number Generators (RNG) are available nowadays; they are divided in two categories, hardware RNG, that provide “true” random numbers, and algorithmic RNG, that generate pseudo random numbers (PRNG). Both types usually generate random numbers (Xn)n as independent uniform samples in a range 0, . . . 2 − 1, with b = 8, 16, 32 or b = 64. In applications, it is instead sometimes desirabl...