NN
2007
Springer
13 years 4 months ago
2007
Springer
The temporal evolution of nearshore sandbars (alongshore ridges of sand fringing coasts in water depths less than 10 m and of paramount importance for coastal safety) is commonly ...
SIAMJO
2002
13 years 4 months ago
2002
Abstract. Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective...
NECO
2002
13 years 4 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
NECO
1998
13 years 4 months ago
1998
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
IJON
2002
13 years 4 months ago
2002
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
TSP
2008
13 years 4 months ago
2008
We propose Gaussian processes for regression as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimat...
TNN
2008
13 years 4 months ago
2008
Prior knowledge over general nonlinear sets is incorporated into nonlinear kernel classification problems as linear constraints in a linear program. The key tool in this incorpora...
TITB
2008
13 years 4 months ago
2008
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
SYNTHESE
2008
13 years 4 months ago
2008
Recent developments in nonlinear dynamics have found wide application in many areas of science from physics to neuroscience. Nonlinear phenomena such as feedback loops, inter-leve...
AUTOMATICA
2006
13 years 5 months ago
2006
This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of g...