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Nonlinear Model Reduction by Moment Matching

complete fashion, moment matching techniques for nonlinear systems. This includes extensive sections on nonlinear time-delay systems; moment;

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Theory of Power Matching

of nonlinear, dynamic power matching with applications, and the most general solution that is not realizable.;

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A Mathematical Modeling Approach from Nonlinear Dynamics to Complex Systems

based on a nonlinear dynamical systems approach that can be used to model and understand complex behavior in nonlinear dynamical systems. It;

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System Reduction for Nanoscale IC Design

of nanoelectronic circuits and suggest model reduction methods for constituting equations. These include linear and nonlinear differential equations;

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System Reduction for Nanoscale IC Design

of nanoelectronic circuits and suggest model reduction methods for constituting equations. These include linear and nonlinear differential equations;

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Dynamics And Nonlinear Control Of Integrated Process Systems

energy integration. Step-by-step model reduction procedures are developed to derive nonlinear reduced models of the dynamics in each time scale;

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Krylov Subspace Methods

subspace methods can be viewed as matching moments model;

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Nonlinear System Identification

autoregressive moving average with exogenous inputs) model * The orthogonal least squares algorithm that allows models to be built term by term where the;

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Mathematical models for the simulation of combined depth and cake filtration processes.

parameters, two different tools are introduced, namely model reduction and parameter identification. Model reduction is used to study the sensitivity;

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Neural Networks for Applied Sciences and Engineering

forecasting Illustrates all stages of model development and interpretation of results, including data preprocessing, data dimensionality reduction;

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Model Reduction of Complex Dynamical Systems

time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on;

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The Bending Theory of Fully Nonlinear Beams

in which the longitudinal bending is accompanied by the transversal deformation of cross-sections. The results provided by the theoretical model;

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Nonlinear Dimensionality Reduction

summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all;

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Nonlinear Dimensionality Reduction

summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all;

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Nonlinear Reaction-Diffusion-Convection Equations

It is well known that symmetry-based methods are very powerful tools for investigating nonlinear partial differential equations (PDEs;

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Introduction to Multivariate Analysis

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling;

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Introduction to Multivariate Analysis

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows;

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Rogue Waves

bilinear transformations, algebro-geometric reduction, and inverse scattering and similarity transformations. Studies on nonlinear optics are;

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Nonlinear Principal Component Analysis and Its Applications

any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the;

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Model Reduction for Control System Design

practising control engineers and graduates for intelligent use of commercial software modules for model and controller reduction.;

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Model Reduction for Control System Design

practising control engineers and graduates for intelligent use of commercial software modules for model and controller reduction.;

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Explicit Nonlinear Model Predictive Control

, resulting in different NMPC problem formulations: O Nonlinear systems described by first-principles models and nonlinear systems described by;

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Modeling and Characterization of RF and Microwave Power FETs

technology-independent approach is described, addressing thermal effects, scaling issues, nonlinear modeling, and in-package matching networks. These;

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Modeling and Characterization of RF and Microwave Power FETs

technology-independent approach is described, addressing thermal effects, scaling issues, nonlinear modeling, and in-package matching networks. These;

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Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images

noiseless or noisy data, reduction will be made. A method which reduces model information or noise was proposed in the reference vol. 376 in LNCIS;

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Model Order Reduction for Efficient EMC Simulation

Model Order Reduction for Efficient EMC Simulation is een boek van Cuvillier Verlag;

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Real Time Computing with the Parareal Algorithm

dependent nonlinear partial differential equations and solving these equations with a coupled approach of combining model reduction and the parareal;

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