In many areas of research and industrial situations, including many data analytic problems in chemistry, a strong nonlinear relation between different sets of data may exist. While linear models may be a good simple approximation to these problems, when nonlinearity is severe they often perform unacceptably. The nonlinear partial least squares (PLS) method was developed in the area of chemical ...

BACKGROUND AND PURPOSE Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusi...

Measurements of HIV1-RNA plasma concentrations are an important method of assessing patient response to anti-HIV1 treatments, and in most clinical trials of such treatments these plasma concentrations are assessed at regular intervals of time. HIV1-RNA plasma levels in successfully treated patients tend to follow a standard pattern, which shows a relatively rapid early decline in viral load, fo...

A new procedure for fitting nonlinear hearing aids (National Acoustic Laboratories' nonlinear fitting procedure, version 1 [NAL-NL1]) is described. The rationale is to maximize speech intelligibility while constraining loudness to be normal or less. Speech intelligibility is predicted by the Speech Intelligibility Index (SII), which has been modified to account for the reduction in performance ...

The problem of tolerant data fitting by a nonlinear surface, induced by a kernel-based support vector machine [19], is formulated as a linear program with fewer number of variables than that of other linear programming formulations [17]. A generalization of the linear programming chunking algorithm [1] for arbitrary kernels [10] is implemented for solving problems with very large datasets where...

In order to design and optimize high-linearity power amplifier (PA), which with nonlinear and memory effect, it is very important to build power amplifier behavior modeling accurately. This paper proposes a power amplifier behavior modeling based on RBF neural network with improved chaos particle swarm optimization algorithm. To make the particles evenly distribute in the problem search space, ...

Varying coefficient models have been widely used in longitudinal data analysis, nonlinear time series, survival analysis, and so on. They are natural non-parametric extensions of the classical linear models in many contexts, keeping good interpretability and allowing us to explore the dynamic nature of the model. Recently, penalized estimators have been used for fitting varying-coefficient mode...

This study proposed a novel Nonlinear Auto Regressive eXogenous Neural Network (NARXNN) with Tracking Signal (TS) approach and seeks to investigate the various training functions to forecast the closing index of the stock market. A novel approach strives to adjust the number of hidden neurons of a NARXNN model with different training functions. It uses the Tracking Signal (TS) and rejects all m...

The present study examined the phenomenon of acclimatization in persons with a severe-to-profound hearing loss. A secondary purpose was to examine the efficacy of a digital nonlinear power hearing aid that has a low compression threshold with expansion for this population. Twenty experienced hearing aid users wore the study hearing aids for three months and their performance with the study hear...

Coral mud is widely distributed in the South China Sea. Studying deformation laws of coral important to infrastructure development In this article, a one-dimensional oedometer test under near-natural conditions performed. The exponential fitting model, Burgers model and ODGM are used analyse time-strain relationship different vertical pressures. self-fitting accuracy prediction three models pre...