Model selection approaches for non-linear system identification: a review
The identification of non-linear systems using only observed finite datasets has become a
mature research area over the last two decades. A class of linear-in-the-parameter models …
mature research area over the last two decades. A class of linear-in-the-parameter models …
Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation
Direct electrical stimulation can modulate the activity of brain networks for the treatment of
several neurological and neuropsychiatric disorders and for restoring lost function. However …
several neurological and neuropsychiatric disorders and for restoring lost function. However …
Nonlinear black-box modeling in system identification: a unified overview
A nonlinear black-box structure for a dynamical system is a model structure that is prepared
to describe virtually any nonlinear dynamics. There has been considerable recent interest in …
to describe virtually any nonlinear dynamics. There has been considerable recent interest in …
Nonlinear black-box modeling in system identification: a unified overview
A nonlinear black-box structure for a dynamical system is a model structure that is prepared
to describe virtually any nonlinear dynamics. There has been considerable recent interest in …
to describe virtually any nonlinear dynamics. There has been considerable recent interest in …
[图书][B] Bayesian methods for nonlinear classification and regression
DGT Denison, CC Holmes, BK Mallick, AFM Smith - 2002 - books.google.com
Nonlinear Bayesian modelling is a relatively new field, but one that has seen a recent
explosion of interest. Nonlinear models offer more flexibility than those with linear …
explosion of interest. Nonlinear models offer more flexibility than those with linear …
[图书][B] Computational intelligence in time series forecasting: theory and engineering applications
AK Palit, D Popovic - 2006 - books.google.com
Foresight can be crucial in process and production control, production-and-resources
planning and in management decision making generally. Although forecasting the future …
planning and in management decision making generally. Although forecasting the future …
Wavelet neural networks: A practical guide
AK Alexandridis, AD Zapranis - Neural Networks, 2013 - Elsevier
Wavelet networks (WNs) are a new class of networks which have been used with great
success in a wide range of applications. However a general accepted framework for …
success in a wide range of applications. However a general accepted framework for …
Limits of estimating heterogeneous treatment effects: Guidelines for practical algorithm design
Estimating heterogeneous treatment effects from observational data is a central problem in
many domains. Because counterfactual data is inaccessible, the problem differs …
many domains. Because counterfactual data is inaccessible, the problem differs …
Dynamic wavelet neural network model for traffic flow forecasting
Accurate and timely forecasting of traffic flow is of paramount importance for effective
management of traffic congestion in intelligent transportation systems. In this paper, a novel …
management of traffic congestion in intelligent transportation systems. In this paper, a novel …