Example: The stationary Poisson process has a constant rate λ > 0 of customer arrivals. This means the interarrival time A between two consecutive customers is an exponential random variable with the cumulative distribution function A(t) = 1 − e. In order to generate the times of arrivals t1, t2, . . . of customer 1, 2, . . . starting from time t0, we use the inverse transform A−1 recursively.

We propose a new test of the critical earthquake model based on the hypothesis that precursory earthquakes are “actors” that create fluctuations in the stress field which exhibit an increasing correlation length as the critical large event becomes imminent. Our approach constitutes an attempt to build a more physically-based cumulative function in the spirit of but improving on the cumulative B...

We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the He...