Abstract We study the extremal properties of a stochastic process x t defined by Langevin equation x ̇ t <m...

The aim of Part II of this paper is to try to describe wave functions on q-deformed versions of position and momentum space. This task is done within the framework developed in Part I of the paper. In order to make Part II self-contained the most important results of Part I are reviewed. Then it is shown that q-deformed exponentials and q-deformed delta functions play the role of momentum and p...

This paper compares three related measures of complexity, ApEn, SampEn, and FuzzyEn. Since vectors' similarity is defined on the basis of the hard and sensitive boundary of Heaviside function in ApEn and SampEn, the two families of statistics show high sensitivity to the parameter selection and may be invalid in case of small parameter. Importing the concept of fuzzy sets, we developed a new me...

It is shown that high order feedforward neural nets of constant depth with piecewise polynomial activation functions and arbitrary real weights can be simulated for boolean inputs and outputs by neural nets of a somewhat larger size and depth with heaviside gates and weights from f?1; 0; 1g. This provides the rst known upper bound for the computational power of the former type of neural nets. I...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

    In this research in order to frequency analysis of maximum daily rainfall in various climates of Iran the data of 40 synoptic rain gauges collected in 40 years period i.e., 1973 to 2012 were used. These stations are located in various climates of Iran according to De Martonne climatic classification. At first, input of data to HYFA package was performed. The mentioned package includes seven...

Gradient-based parameter optimization is commonly used for training neural networks and optimizing the performance of other complex systems that only contain continuously differentiable functions. However, there is a large class of important parameter optimization problems involving systems containing discretevalued functions that do not permit the direct use of gradient-based methods. Examples...