Abstract. We present a simple dynamical model to address the question of introducing a stochastic nature in a time variable. This model includes noise in the time variable but not in the “space" variable, which is opposite to the normal description of stochastic dynamics. The notable feature is that these models can induce a “resonance" with varying noise strength in the time variable. Thus, th...

A number of multi-priority jobs are to be processed on two heterogeneous processors. Of the jobs waiting in the buffer, jobs with the highest priority have the first option of being dispatched for processing when a processor becomes available. On each processor, the processing times of the jobs within each priority class are stochastic, but have known distributions with decreasing mean residual...

acrylamide was grafted in low density polyethylene during melt processing in the presence of a free radical initiator using a torque rheometer in a closed system. effects of processing time, acrylamide and benzoyl peroxide concentrations were studied. ftir studies revealed that the degree of grafting increased by an increase in acrylamide concentration. maximum grafting was obtained at 7 minute...

The goal of this paper is to introduce a complete analysis/resynthesis method for the stationary part of voiced-sounds. The method is based on a new class of wavelets, the Harmonic-Band Wavelets (HBWT). Wavelets have been widely employed in signal processing [1, 2]. In the context of sound processing they provided very interesting results in their first harmonic version: the Pitch Synchronous W...

It is known that a stochastic differential equation (SDE) induces two probabilistic objects, namely a difusion process and a stochastic flow. While the diffusion process is determined by the innitesimal mean and variance given by the coefficients of the SDE, this is not the case for the stochastic flow induced by the SDE. In order to characterize the stochastic flow uniquely the innitesimal cov...

Robust learning rules in case of ill-conditioned problems for neural PCAand ICA-networks with adaptation of the learning rates Methods for Blind Signal Processing (BSP) are becoming noticeably more important. Amongst others, these techniques are applied in biomedical signal processing, image processing and speech processing. Within the BSP, the Principal Component Analysis (PCA) and the Indepen...

Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the sizes of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated machine scheduling model with stochastic processing times of jobs. By means of a novel time-indexed linear ...