Hierarchical f u q neural networks can use less rules to model nonlinear system with high accuracy. But the structure is very complex, the normal training for hierarchical fuzzy neural networks is difficult to realize. In this paper we use backpropagation-like approach to train the membership functions. The new learning schemes employ a time-varying learning rate that is determined from input-o...

This paper presents a new method to estimate the region of stability of an asymptotically stable equilibrium point of an autonomous nonlinear system using a neural network. In contrast to model-based analytical methods, this approach uses empirical data from the system to train the neural network. The neural network results are compared with estimates obtained by previously proposed methods for...

We present a new laser system and nonlinear microscope, designed for differential nonlinear microscopy. The microscope features time-correlated single photon counting of multiphoton fluorescence generated by an alternating pulse-train of orthogonally polarized pulses. The generated nonlinear signal is separated using home-built electronics. Results are presented on fluorescence-detected nonline...

Poisson processes usually provide adequate descriptions of the irregularity in neuron spike times after pooling the data across large numbers of trials, as is done in constructing the peristimulus time histogram. When probabilities are needed to describe the behavior of neurons within individual trials, however, Poisson process models are often inadequate. In principle, an explicit formula give...

Statistical measures of determinism for spikes train are described and analyzed. The analysis is focused on two dynamical invariants: nonlinear forecastability and correlation dimension. Two simple, generic, biologically motivated methods for generating spikes from the system are surveyed: an integrate-and-fire model (IF) and a threshold-crossing method (TC). The effect on the statistical measu...

The peristaltic flow of a Jeffrey fluid with variable viscosity through a porous medium in an asymmetric channel is investigated. The channel asymmetric is produced by choosing the peristaltic wave train on thewall of different amplitude and phase. The governing nonlinear partial differential equations for the Jeffrey fluid model are derived in Cartesian coordinates system. Analytic solutions f...

The cubic nonlinear Schroedinger equation (NLS) describes the space-time evolution of narrow-banded wave trains in one space and one time (1 + 1) dimensions. The richness of nonlinear wave motions described by NLS is exemplified by the fully nonlinear envelope soliton and “breather” solutions, which are fully understood only in terms of the general solution of the equation as described by the i...

Railway scheduling is a complex task of rail operators that involves the generation of a conflict-free train timetable. This paper presents a discrete-event simulation-based optimization approach for solving the train timetabling problem to minimize total weighted unplanned stop time in a hybrid single and double track railway networks. The designed simulation model is used as a platform for ge...

Abstract. The Benjamin-Feir instability describes the instability of a uniform oscillatory wave train in an irrotational flow subject to small perturbation of wave number, amplitude and frequency. Their instability analysis is based on the perturbation around the second order Stokes wave which satisfies the dynamic and kinematic free-surface boundary conditions up to the second order. In the sa...

OBJECTIVE Nonlinear system identification approaches were used to develop a dynamical model of the network level response to patterns of microstimulation in vivo. APPROACH The thalamocortical circuit of the rodent vibrissa pathway was the model system, with voltage sensitive dye imaging capturing the cortical response to patterns of stimulation delivered from a single electrode in the ventral...