Mathematical theory exists, in principle, for exploring broader classes of perturbation though in practice the complexity of biological systems frustrates deep analytical insights.
The main contribution of our work is that we propose a computational approach for and an implementation of the automatic estimation of the robustness that applies to a broad class of dynamical properties and a large variety of possible perturbations.
In all, the paper illustrates how the path-integral representation provides a unifying framework for a plethora of asymptotic perturbation methods applicable to a broad class of hybrid stochastic neural network models.
The superiorization method can solve a broad class of nonlinear constrained optimal problems, which works by using the bounded perturbation resilience (BPR) of an original algorithm in order to steer the iterates of the algorithm towards to lower values of the objective function.
Neuromuscular exercise is a relatively broad class of exercise programs incorporating programs known by terms such as functional exercise, proprioceptive, agility, or perturbation training.
This criterion is not only applicable to a broad class of infinite-dimensional systems with periodic nonlinearities, but in fact ensures the equilibria set stability under singular perturbation.
We show that for a broad class of r.i.
This relaxation leads to a broad class of spaces.
Such variation covers a fairly broad class of graded materials.
Dietary fiber represents a broad class of undigested carbohydrate components.
