Most functional magnetic resonance imaging studies use linear models to predict the measured response by convolution of an impulse response with the stimulus profile. Using very short visual presentation times (<2 s), deviation from the linear model in the measured BOLD data from the human brain was found for the response integral, amplitude, and width. In this study, high temporal and spatial ...

The nonlinearity index is a measure of the nonlinearity of dynamical systems based on computing the initial-condition sensitivity of the statetransition matrix. The Cayley form is a representation for dynamical systems that relates their motion to N -dimensional rotations. The generalized coordinates of the system are used to define an N -dimensional orientation, and a set of quasi velocities i...

The nonlinearity index is a measure of the nonlinearity of dynamical systems based on computing the initial-condition sensitivity of the state-transition matrix. The Cayley form is a representation for dynamical systems that relates their motion to N-dimensional rotations. The generalized coordinates of the system are used to define an N-dimensional orientation, and a set of quasi velocities is...

Abstract. The dynamics of a membrane is a coupled system of a moving elastic surface and an incompressible membrane fluid. The difficulties in analyzing such a system include the nonlinearity of the curved space (geometric nonlinearity), the nonlinearity of the fluid dynamics (fluid nonlinearity), and the coupling to the surface incompressibility. In the two-dimensional case, the fluid vanishes...

piezoelectric actuators are widely used in micro manipulation applications. however hysteresis nonlinearity limits accuracy of these actuators. this paper presents a novel approach utilizing a piezoelectric nano-stage as slave manipulator of a teleoperation system. the prandtl-ishlinskii (pi) model is used to model actuator hysteresis in feedforward scheme to cancel out this nonlinearity. a pas...

Most functional magnetic resonance imaging studies use linear models to predict the measured response by convolution of an impulse response with the stimulus profile. Using very short visual presentation times ( 2 s), deviation from the linear model in the measured BOLD data from the human brain was found for the response integral, amplitude, and width. In this study, high temporal and spatial ...

One attractive aspect of optical fibers is their enormous bandwidth compared to other media, such as radio waves and twisted-pair wires. Still, an optical fiber is not ideal; it possesses some unwanted properties. Dispersion and nonlinearity are the major limiting factors in lightwave communication. Fiber dispersion causes different spectral components of a signal to travel at different speeds....

The enhancement of the optical nonlinear effects at nanoscale is important in the on-chip optical information processing. We theoretically propose the mechanism of the great Kerr nonlinearity enhancement by using anisotropic Purcell factors in a double-Λ type four-level system, i.e., if the bisector of the two vertical dipole moments lies in the small/large Purcell factor axis in the space, the...

A general method is presented for modeling spatially extended systems that may contain a localized source of nonlinearity. It has direct applications to structural health monitoring (SHM) where physical damage may cause such nonlinearity and also communications channels which may exhibit localized nonlinearity due to bad electrical contacts or component nonlinearity. The method uses a multistag...

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...