Scalar time domain modeling and coupling of second harmonic generation process in GaAs discontinuous optical waveguide

We present in this work the scalar potential formulation of second harmonic generation process in chi((2)) nonlinear analysis. This approach is intrinsically well suited to the applications of the concept of circuit analysis and synthesis to nonlinear optical problems, and represents a novel alternative method in the analysis of nonlinear optical waveguide, by providing a good convergent numerical solution. The time domain modeling is applied to nonlinear GaAs asymmetrical waveguide with dielectric discontinuities in the hypothesis of quasi phase matching condition in order to evaluate the efficiency conversion of the second harmonic signal. The accuracy of the modeling is validated by the good agreement with the published experimental results. The effective dielectric constant method allows to extend the analysis also to 3D optical waveguides. (c) 2008 Optical Society of America

Identification method based on Zadeh filter models

Mathematical modeling which provides the description of objects and proper organization of control operations in future is an integral stage in the automation of production. One of the approaches to build a mathematical model of an object is to represent nonlinear systems as combinations of inertial and nonlinear inertialess elements. The models thus obtained are called block-oriented. In this paper, we consider nonlinear dynamic objects represented as the models of the Zadeh filter class. In the process of the method development the identification equations were derived for the case when the test signal is a single sinusoid. Then the case of two sinusoids was considered. Such investigations allowed us to identify the patterns and describe the general case for several test components in the signal. The results of digital modeling using the sum of harmonic signals confirm the feasibility and validity of the proposed approach for identifying nonlinear models of the Zadeh filter class

Power waves formulation of oscillation conditions: avoidance of bifurcation modes in cross-coupled VCO architectures

This paper discusses necessity of power-waves formulation to extend voltage-current oriented approaches based on linear concepts such as admittance/impedance operators and transfer-function representations. Importance of multi-physics methodologies, throughout power-waves formulation, for the analysis and design of crystal oscillators is discussed. Interpretation of bifurcation modes in differential cross-coupled VCO architectures in terms of gyrator-like behavior, is proposed. Impact of amplitude level control (ALC) on large-signal phase noise performances is underlined showing necessity of robust control analysis approach relative to power-energy considerations

Physics-based large-signal sensitivity analysis of microwave circuits using technological parametric sensitivity from multidimensional semiconductor device models

The authors present an efficient approach to evaluate the large-signal (LS) parametric sensitivity of active semiconductor devices under quasi-periodic operation through accurate, multidimensional physics-based models. The proposed technique exploits efficient intermediate mathematical models to perform the link between physics-based analysis and circuit-oriented simulations, and only requires the evaluation of dc and ac small-signal (dc charge) sensitivities under general quasi-static conditions. To illustrate the technique, the authors discuss examples of sensitivity evaluation, statistical analysis, and doping profile optimization of an implanted MESFET to minimize intermodulation which makes use of LS parametric sensitivities under two-tone excitatio

Nonlinear mechanisms in passive microwave devices

Premi extraordinari doctorat curs 2010-2011, àmbit d’Enginyeria de les TICThe telecommunications industry follows a tendency towards smaller devices, higher power and higher frequency, which imply an increase on the complexity of the electronics involved. Moreover, there is a need for extended capabilities like frequency tunable devices, ultra-low losses or high power handling, which make use of advanced materials for these purposes. In addition, increasingly demanding communication standards and regulations push the limits of the acceptable performance degrading indicators. This is the case of nonlinearities, whose effects, like increased Adjacent Channel Power Ratio (ACPR), harmonics, or intermodulation distortion among others, are being included in the performance requirements, as maximum tolerable levels. In this context, proper modeling of the devices at the design stage is of crucial importance in predicting not only the device performance but also the global system indicators and to make sure that the requirements are fulfilled. In accordance with that, this work proposes the necessary steps for circuit models implementation of different passive microwave devices, from the linear and nonlinear measurements to the simulations to validate them. Bulk acoustic wave resonators and transmission lines made of high temperature superconductors, ferroelectrics or regular metals and dielectrics are the subject of this work. Both phenomenological and physical approaches are considered and circuit models are proposed and compared with measurements. The nonlinear observables, being harmonics, intermodulation distortion, and saturation or detuning, are properly related to the material properties that originate them. The obtained models can be used in circuit simulators to predict the performance of these microwave devices under complex modulated signals, or even be used to predict their performance when integrated into more complex systems. A key step to achieve this goal is an accurate characterization of materials and devices, which is faced by making use of advanced measurement techniques. Therefore, considerations on special measurement setups are being made along this thesis.Award-winningPostprint (published version

Neural-Based Nonlinear Device Models for Intermodulation Analysis

A new procedure to learn a nonlinear model together with its derivative parameters using a composite neural network is presented.So far neural networks have never been used to extract large-signal device model accounting for distortion parameters.Applying this method to FET devices leads to nonlinear models for current- voltage functions which allow improved prediction of weak and mildly device nonlinearities in the whole bias region. The resulting models have demonstrated to be suitable for both small-signal and large-signal analyses,including intermodulation distortion prediction

Deep Learning-Based Wave Digital Modeling of Rate-Dependent Hysteretic Nonlinearities for Virtual Analog Applications

Electromagnetic components greatly contribute to the peculiar timbre of analog audio gear. Indeed, distortion effects due to the nonlinear behavior of magnetic materials are known to play an important role in enriching the harmonic content of an audio signal. However, despite the abundant research that has been devoted to the characterization of nonlinearities in the context of virtual analog modeling over the years, the discrete-time simulation of circuits exhibiting rate-dependent hysteretic phenomena remains an open challenge. In this article, we present a novel data-driven approach for the wave digital modeling of rate-dependent hysteresis using recurrent neural networks (RNNs). Thanks to the modularity of wave digital filters, we are able to locally characterize the wave scattering relations of a hysteretic reluctance by encapsulating an RNN-based model into a single one-port wave digital block. Hence, we successfully apply the proposed methodology to the emulation of the output stage of a vacuum-tube guitar amplifier featuring a nonlinear transformer