Search results for "nonlinear"
showing 10 items of 3684 documents
The hidden group structure of quantum groups: strong duality, rigidity and preferred deformations
1994
A notion of well-behaved Hopf algebra is introduced; reflexivity (for strong duality) between Hopf algebras of Drinfeld-type and their duals, algebras of coefficients of compact semi-simple groups, is proved. A hidden classical group structure is clearly indicated for all generic models of quantum groups. Moyal-product-like deformations are naturally found for all FRT-models on coefficients andC∞-functions. Strong rigidity (H bi 2 ={0}) under deformations in the category of bialgebras is proved and consequences are deduced.
Heteroclinic contours and self-replicated solitary waves in a reaction–diffusion lattice with complex threshold excitation
2008
Abstract The space–time dynamics of the network system modeling collective behavior of electrically coupled nonlinear cells is investigated. The dynamics of a local cell is described by the FitzHugh–Nagumo system with complex threshold excitation. Heteroclinic orbits defining traveling wave front solutions are investigated in a moving frame system. A heteroclinic contour formed by separatrix manifolds of two saddle-foci is found in the phase space. The existence of such structure indicates the appearance of complex wave patterns in the network. Such solutions have been confirmed and analyzed numerically. Complex homoclinic orbits found in the neighborhood of the heteroclinic contour define …
Evaluation of enantioselective binding of fluoxetine to human serum albumin by ultrafiltration and CE - Experimental design and quality considerations
2012
Several pharmacokinetic processes are affected by enantioselectivity (ES). At the level of distribution, protein binding (PB) is one of the most important. The enantioselective binding of fluoxetine (FLX) to HSA has been evaluated in this work by ultrafiltration of FLX–HSA mixtures and chiral analysis of unbound fractions by EKC-CD. PB, affinity constants (K) and ES were obtained for both enantiomers of FLX. In order to improve the consistency of the estimations, the evaluation of affinity constants of each enantiomer was performed using two designs, one keeping constant the total concentration of protein and varying the total concentration of the enantiomers, and the other in the opposite …
Efficient unsupervised clustering for spatial bird population analysis along the Loire river
2015
International audience; This paper focuses on application and comparison of Non Linear Dimensionality Reduction (NLDR) methods on natural high dimensional bird communities dataset along the Loire River (France). In this context, biologists usually use the well-known PCA in order to explain the upstream-downstream gradient.Unfortunately this method was unsuccessful on this kind of nonlinear dataset.The goal of this paper is to compare recent NLDR methods coupled with different data transformations in order to find out the best approach. Results show that Multiscale Jensen-Shannon Embedding (Ms JSE) outperform all over methods in this context.
Making nonlinear manifold learning models interpretable: The manifold grand tour
2015
Smooth nonlinear topographic maps of the data distribution to guide a Grand Tour visualisation.Prioritisation of data linear views that are most consistent with data structure in the maps.Useful visualisations that cannot be obtained by other more classical approaches. Dimensionality reduction is required to produce visualisations of high dimensional data. In this framework, one of the most straightforward approaches to visualising high dimensional data is based on reducing complexity and applying linear projections while tumbling the projection axes in a defined sequence which generates a Grand Tour of the data. We propose using smooth nonlinear topographic maps of the data distribution to…
Dimensionality reduction via regression on hyperspectral infrared sounding data
2014
This paper introduces a new method for dimensionality reduction via regression (DRR). The method generalizes Principal Component Analysis (PCA) in such a way that reduces the variance of the PCA scores. In order to do so, DRR relies on a deflationary process in which a non-linear regression reduces the redundancy between the PC scores. Unlike other nonlinear dimensionality reduction methods, DRR is easy to apply, it has out-of-sample extension, it is invertible, and the learned transformation is volume-preserving. These properties make the method useful for a wide range of applications, especially in very high dimensional data in general, and for hyperspectral image processing in particular…
Active spike transmission in the neuron model with a winding threshold manifold
2012
International audience; We analyze spiking responses of excitable neuron model with a winding threshold manifold on a pulse stimulation. The model is stimulated with external pulse stimuli and can generate nonlinear integrate-and-fire and resonant responses typical for excitable neuronal cells (all-or-none). In addition we show that for certain parameter range there is a possibility to trigger a spiking sequence with a finite number of spikes (a spiking message) in the response on a short stimulus pulse. So active transformation of N incoming pulses to M (with M>N) outgoing spikes is possible. At the level of single neuron computations such property can provide an active "spike source" comp…
A nonlinear electronic circuit mimicking the neuronal activity in presence of noise
2013
We propose a nonlinear electronic circuit simulating the neuronal activity in a noisy environment. This electronic circuit is ruled by the set of Bonhaeffer-Van der Pol equations and is excited with a white gaussian noise, that is without external deterministic stimuli. Under these conditions, our circuits reveals the Coherence Resonance signature, that is an optimum of regularity in the system response for a given noise intensity.
Integrable systems, Frobenius manifolds and cohomological field theories
2022
In this dissertation, we study the underlying geometry of integrable systems, in particular tausymmetric bi-Hamiltonian hierarchies of evolutionary PDEs and differential-difference equations.First, we explore the close connection between the realms of integrable systems and algebraic geometry by giving a new proof of the Witten conjecture, which constructs the string taufunction of the Korteweg-de Vries hierarchy via intersection theory of the moduli spaces of stable curves with marked points. This novel proof is based on the geometry of double ramification cycles, tautological classes whose behavior under pullbacks of the forgetful and gluing maps facilitate the computation of intersection…
A numerical study of attraction/repulsion collective behavior models: 3D particle analyses and 1D kinetic simulations
2013
39p; International audience; We study at particle and kinetic level a collective behavior model based on three phenomena: self-propulsion, friction (Rayleigh effect) and an attractive/repulsive (Morse) potential rescaled so that the total mass of the system remains constant independently of the number of particles N . In the first part of the paper, we introduce the particle model: the agents are numbered and described by their position and velocity. We iden- tify five parameters that govern the possible asymptotic states for this system (clumps, spheres, dispersion, mills, rigid-body rotation, flocks) and perform a numerical analysis on the 3D setting. Then, in the second part of the paper…