Search results for "Nonlinear dynamic"
showing 10 items of 158 documents
Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis
2016
Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…
PRINCIPAL POLYNOMIAL ANALYSIS
2014
© 2014 World Scientific Publishing Company. This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves instead of straight lines. Contrarily to previous approaches PPA reduces to performing simple univariate regressions which makes it computationally feasible and robust. Moreover PPA shows a number of interesting analytical properties. First PPA is a volume preserving map which in turn guarantees the existence of the inverse. Second such an inverse can be obtained…
An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions
2020
Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…
Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm
2016
Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…
Asymptotic regime in N random interacting species
2005
The asymptotic regime of a complex ecosystem with \emph{N}random interacting species and in the presence of an external multiplicative noise is analyzed. We find the role of the external noise on the long time probability distribution of the i-th density species, the extinction of species and the local field acting on the i-th population. We analyze in detail the transient dynamics of this field and the cavity field, which is the field acting on the $i^{th}$ species when this is absent. We find that the presence or the absence of some population give different asymptotic distributions of these fields.
Resonant activation in piecewise linear asymmetric potentials
2011
7 páginas, 8 figuras.-- PACS number(s): 05.40.−a, 05.45.−a, 02.50.Ey
A Galerkin approach for power spectrum determination of nonlinear oscillators
2002
A numerical method to estimate spectral properties of nonlinear oscillators with random input is presented. The stationary system response is expanded into a trigonometric Fourier series. A set of nonlinear algebraic equations, solved by Newton's method, leads to the determination of the unknown Fourier series coefficients of single samples of the response process. For cubic polynomial nonlinearities, closed-form expressions are used to find the nonlinear terms at each step of the solution scheme. Further, a simple procedure yields an approximation of an arbitrary nonlinearity by a cubic polynomial. Power spectral density estimates for the response process are constructed by averaging the s…
Mathematical modeling of oral absorption and bioavailability of a fluoroquinolone after its precipitation in the gastrointestinal tract
2013
The objective was to characterize the in vivo absorption and bioavailability (BA) of a low solubility, high permeability fluoroquinolone (CNV97101) that precipitates in the gastrointestinal (GI) tract by mathematical modeling approach. In situ rat intestinal perfusion studies were performed to characterize the absorption mechanism. The oral fraction absorbed in vivo was lower than the predicted based on the in situ intestinal permeability. Two additional routes of administration, intraduodenal (ID) and intraperitoneal (IP) were investigated to explore if precipitation in stomach and subsequent partial re-dissolution were the causes of the lower in vivo BA. Ex vivo precipitation studies with…
Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds
1998
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
Erratum: “The Role of Humidity in Associations of High Temperature with Mortality: A Multicountry, Multicity Study”
2019
There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature.We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset.In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific as…