Nonlinear microscopy is widely used to characterize thick, optically heterogeneous biological samples. While quantitative image analysis requires accurately describing the contrast mechanisms at play, majority of established numerical models neglect influence field distortion caused by sample heterogeneity near focus. In this work, we show experimentally and numerically that finite-difference t...

This paper presents an ultrasonic transducer modeling with VHDL-AMS standard (Very High speed integrated circuits Hardware Description Language – Analog and Mixed Signal) referenced IEEE 1076.1, integrated in a global measurement cell modeling dedicated to biological tissues ultrasound characterization. Usual modeling of ultrasonic transducer are based on electrical analogy and are not simulate...

Many kinetic plasma instabilities, in quite di erent physical systems, share a genuinely similar mathematical structure near isolated phase-space islands. For this reason, dynamical features such as faster-than-exponential growth of the instability, as well as nonlinear frequency sweeping, are found to be universal. Numerical f methods, which follow the evolution of the (nonlinear) perturbed di...

Thermoacoustic systems convert energy from heat to acoustic power and vice versa. These systems have commercial interest due to the high potential efficiency and low number of moving parts. To numerically predict the performance of a thermoacoustic device inherent nonlinearities in the system, such as thermoacoustic streaming and generation of harmonics need to be taken into account. We present...

This research frame work investigates the application of a clustered based Neuro-fuzzy system to nonlinear dynamic system modeling from a set of input-output training patterns. It is concentrated on the modeling via Takagi-Sugeno (T-S) modeling technique and the employment of fuzzy clustering to generate suitable initial membership functions. Hence, such created initial memberships are then emp...

This chapter presents a method of determining electromotive force (EMF) and battery internal resistance as time functions, which are depicted as functions of state of charge (SOC). The model is based on battery discharge and charge characteristics under different constant currents that are tested by a laboratory experiment. Further the method of determining the battery SOC according to the batt...

The investigation of flutter and aeroservoelastic stability through flight testing is an essential part of aircraft certification. The stability boundary prediction is especially difficult when the instability is associated with nonlinearity in the dynamics. This paper presents an approach for the characterization of the nonlinear dynamics by non-iterative identification algorithms. Two differe...

An important aspect of real time glucose control in diabetic subjects is forecasting the future glucose profile. From a modeling perspective, the complexity of interactions between plasma glucose and its controlling hormone insulin, demands a nonlinear modeling approach for representing the dynamics of glucose metabolism. In this paper, a technique based on the hybrid approach of nonlinear auto...

Neural network black-box modeling is usually performed using nonlinear inputoutput models. The goal of this paper is to show that there are advantages in using nonlinear state-space models, which constitute a larger class of nonlinear dynamical models, and their corresponding state-space neural predictors. We recall the fundamentals of both input-output and state-space black-box modeling, and s...