The field of robotics is one of the most innovative in the last decade. Conventional industrial robots from the late 70 ́s are now only a tool on the production level. One of the oldest dreams of the robotic community – intelligent, mobile and humanoid robots – starts to become a reality because of the rapid development of “external” sensors. External sensors (e.g. visual, auditive, force-torque) offer intelligent robots the possibility to see, hear, speak, feel, smell like humans. Compared with conventional, unintelligent, industrial robots, intelligent robots can fulfill new, innovative tasks in new application areas.

Computer Aided Systems Theory - EUROCAST’99

Motivated by a typical and well-known problem of neurobiological modeling, a parallel algorithm devised to simulate sample paths of stationary normal processes with rational spectral densities is implemented to evaluate first passage time probability densities for time-varying boundaries. After a self-contained outline of the original problem and of the involved computational framework, the results of numerous simulations are discussed and conclusions are drawn on the effect of a periodic boundary and a Butterworth-type covariance on determining quantitative and qualitative features of first passage time probability densities.

Simulation of Gaussian Processes and First Passage Time Densities Evaluation

A jump-diffusion process is proposed to describe the displacements performed by single myosin heads along actin filaments during the rising phases. The process consists of the superposition of a Wiener and a jump process, with jumps originated by sequences of Poisson-distributed energysupplying pulses. In a previous paper [6], the amplitude of the jumps was described by a mixture of two Gaussian distributions. To embody the effects of ATP hydrolysis [1], we now refine such a model by assuming that the jumps’ amplitude is described by a mixture of three Gaussian distributions. This model has been inspired by the experimental data of T. Yanagida and his co-workers concerning observations at single molecule processes level as described in [10] and in the references therein.

A stochastic model for the stepwise motion in actomyosin dynamics

The problem of evaluating first crossing probability densities for stationary normal processes possessing a rational spectral density is approached by means of an effective simulation procedure. We focus our attention on the case of pairs of smooth boundaries, a constant and a periodic one, and on processes possessing two-parameter oscillatory covariances. On the base of the results yielded by our simulations, conclusions are drawn on the effects of the periodic components of covariance and boundaries on shape and features of the first crossing densities.

Buonocore Aniello

Papers

A vectorized simulation procedure for computations of first crossing time densities of normal processes with oscillatory covariances

A stochastic model for the rising phase of myosin head displacements along actin filaments