Linear and Nonlinear Response Functions for an Exact State and for an MCSCF State. J. ... AD Buckingham,DA Long - 《Philosophical Transactions of the Royal Society A Mathematical Physical & Engineering Sciences》 被引量: 0发表: 1979年 Analysis of a nonlinear optical response of CN ions ...
Linear regression models describe a linear relationship between a response and one or more predictive terms. Many times, however, a nonlinear relationship exists.Nonlinear Regressiondescribes general nonlinear models. A special class of nonlinear models, calledgeneralized linear models, uses linear methods...
Fig. 2: Linear vs nonlinear models of rsfMRI activity. a, The distribution of cross-validated regional \({R}_{i}^{2}\), combined across all 116 regions and 700 participants, for linear (green) and nonlinear (yellow) models. The grey box corresponds to the zero model used as a baseli...
Polymer-Matrix Composites (PMC); Structural Health Monitoring (SHM); vibration analysis; linear/nonlinear methods 1. Introduction Nowadays, the use of PMCs in industrial sectors, such as aeronautics and the automotive sector, is sharply increasing thanks to their high mechanical properties, low weight...
=== There are some large data for which with/without nonlinear mappings gives similar performances. Without using kernels, one can efficiently train a much larger set via linear classification/regression. These data usually have a large number of features. Document classification is an example...
摘要: In this paper, we describe a class of combined relaxation methods for the non strictly monotone nonlinear variational inequality problem, which involves a max-type convex function. This method is readily implementable and attains a linear rate of convergence under certain additional assumptions....
The linear dynamic block consists of a cascade of time delays, and the nonlinear static structure is that of polynomial terms processing different combinations of delayed input signal samples. Sign in to download full-size image FIGURE 7.13. Diagram representations of the polynomial filter kernels: ...
(GLMM; McCulloch and Searle2001). Even more flexibility about the relationships between the outcome and the predictors has been introduced in the context of the so-called Nonlinear Mixed-Effects Models (Davidian and Giltinan1995). The LCM has also undergone notable extensions. In particular, when...
GeneralizedLinearModelis a fitted generalized linear regression model. A generalized linear regression model is a special class of nonlinear models that describe a nonlinear relationship between a response and predictors. A generalized linear regression model has generalized characteristics of a linear regres...
We demonstrate the design of a neural network hardware, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Weights and interconnections of the network are realized by a magnetic-field pattern that is applie...