- Home | Nonlinear Dynamics - Springer
The journal covers nonlinear dynamics in mechanical, structural, civil, aeronautical, ocean, electrical, control, and hybrid systems Review articles, feature articles and original contributions based on analytical, computational, experimental methods, and data-driven approaches are welcome
- Home | Journal of Nonlinear Science - Springer
The mission of the Journal of Nonlinear Science is to publish papers that augment the fundamental ways we describe, model, and predict nonlinear phenomena It features papers that make an original contribution to at least one technical area and illuminate issues beyond that area's boundaries
- Introduction to Nonlinear Finite Element Analysis
This book introduces the key concepts of nonlinear finite element analysis procedures The book explains the fundamental theories of the field and provides instructions on how to apply the concepts to solving practical engineering problems
- Nonlinear Dynamics: A Concise Introduction Interlaced with Code . . .
This concise and up-to-date textbook provides an accessible introduction to the core concepts of nonlinear dynamics as well as its existing and potential applications
- Nonlinear Optics: Principles and Applications | SpringerLink
This book reflects the latest advances in nonlinear optics Besides the simple, strict mathematical deduction, it also discusses the experimental verification and possible future applications, such as the all-optical switches It consistently uses the practical unit system throughout
- Nonlinear Effect | SpringerLink
That is to say, in a nonlinear system, the input is not proportional to the output Statistically speaking, an effect between a predictor and a dependent variable is called nonlinear if it changes in size or sign depending on the predictor’s own values or depending on the values of other predictors
- Non-linear Techniques for Dimension Reduction | SpringerLink
Summary Two kinds of non-linear dimension reduction techniques, kernel-based methods and manifold learning related algorithms, have been introduced here
- Nonlinear Regression Modelling: A Primer with Applications . . . - Springer
The article is structured as follows To provide important context, Sect 2 introduces simple motivating nonlinear model examples which highlight both nonlinear modelling in practice and underscores key differences with linear models
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