Simultaneous Control of Chaotic Systems Using RBF Networks

Chaos control is a concept that recently acquiring more attention among the research community, concerning the fields of engineering, physics, chemistry, biology and mathematic. This paper presents a method to simultaneous control of deterministic chaos in several nonlinear dynamical systems. A radial basis function networks (RBFNs) has been used to control chaotic trajectories in the equilibrium points. Such neural network improves results, avoiding those problems that appear in other control methods, being also efficient dealing with a relatively small random dynamical noise.

GPS inferred velocity and strain rate fields in eastern Canada

La vallée du fleuve Saint-Laurent, dans l’est du Canada, est l’une des régions sismiques les plus actives dans l’est de l’Amérique du Nord et est caractérisée par de nombreux tremblements de terre intraplaques. Après la rotation rigide de la plaque tectonique, l’ajustement isostatique glaciaire est de loin la plus grande source de signal géophysique dans l’est du Canada. Les déformations et les vitesses de déformation de la croûte terrestre de cette région ont été étudiées en utilisant plus de 14 ans d’observations (9 ans en moyenne) de 112 stations GPS fonctionnant en continu. Le champ de vitesse a été obtenu à partir de séries temporelles de coordonnées GPS quotidiennes nettoyées en appliquant un modèle combiné utilisant une pondération par moindres carrés. Les vitesses ont été estimées avec des modèles de bruit qui incluent les corrélations temporelles des séries temporelles des coordonnées tridimensionnelles. Le champ de vitesse horizontale montre la rotation antihoraire de la plaque nord-américaine avec une vitesse moyenne de 16,8±0,7 mm/an dans un modèle sans rotation nette (no-net-rotation) par rapport à l’ITRF2008. Le champ de vitesse verticale confirme un soulèvement dû à l’ajustement isostatique glaciaire partout dans l’est du Canada avec un taux maximal de 13,7±1,2 mm/an et un affaissement vers le sud, principalement au nord des États-Unis, avec un taux typique de −1 à −2 mm/an et un taux minimum de −2,7±1,4 mm/an. Le comportement du bruit des séries temporelles des coordonnées GPS tridimensionnelles a été analysé en utilisant une analyse spectrale et la méthode du maximum de vraisemblance pour tester cinq modèles de bruit: loi de puissance; bruit blanc; bruit blanc et bruit de scintillation; bruit blanc et marche aléatoire; bruit blanc, bruit de scintillation et marche aléatoire. Les résultats montrent que la combinaison bruit blanc et bruit de scintillation est le meilleur modèle pour décrire la partie stochastique des séries temporelles. Les amplitudes de tous les modèles de bruit sont plus faibles dans la direction nord et plus grandes dans la direction verticale. Les amplitudes du bruit blanc sont à peu près égales à travers la zone d’étude et sont donc surpassées, dans toutes les directions, par le bruit de scintillation et de marche aléatoire. Le modèle de bruit de scintillation augmente l’incertitude des vitesses estimées par un facteur de 5 à 38 par rapport au modèle de bruit blanc. Les vitesses estimées de tous les modèles de bruit sont statistiquement cohérentes. Les paramètres estimés du pôle eulérien de rotation pour cette région sont légèrement, mais significativement, différents de la rotation globale de la plaque nord-américaine. Cette différence reflète potentiellement les contraintes locales dans cette région sismique et les contraintes causées par la différence des vitesses intraplaques entre les deux rives du fleuve Saint-Laurent. La déformation de la croûte terrestre de la région a été étudiée en utilisant la méthode de collocation par moindres carrés. Les vitesses horizontales interpolées montrent un mouvement cohérent spatialement: soit un mouvement radial vers l’extérieur pour les centres de soulèvement maximal au nord et un mouvement radial vers l’intérieur pour les centres d’affaissement maximal au sud, avec une vitesse typique de 1 à 1,6±0,4 mm/an. Cependant, ce modèle devient plus complexe près des marges des anciennes zones glaciaires. Basées selon leurs directions, les vitesses horizontales intraplaques peuvent être divisées en trois zones distinctes. Cela confirme les conclusions d’autres chercheurs sur l’existence de trois dômes de glace dans la région d’étude avant le dernier maximum glaciaire. Une corrélation spatiale est observée entre les zones de vitesses horizontales intraplaques de magnitude plus élevée et les zones sismiques le long du fleuve Saint-Laurent. Les vitesses verticales ont ensuite été interpolées pour modéliser la déformation verticale. Le modèle montre un taux de soulèvement maximal de 15,6 mm/an au sud-est de la baie d’Hudson et un taux d’affaissement typique de 1 à 2 mm/an au sud, principalement dans le nord des États-Unis. Le long du fleuve Saint-Laurent, les mouvements horizontaux et verticaux sont cohérents spatialement. Il y a un déplacement vers le sud-est d’une magnitude d’environ 1,3 mm/an et un soulèvement moyen de 3,1 mm/an par rapport à la plaque l’Amérique du Nord. Le taux de déformation verticale est d’environ 2,4 fois plus grand que le taux de déformation horizontale intraplaque. Les résultats de l’analyse de déformation montrent l’état actuel de déformation dans l’est du Canada sous la forme d’une expansion dans la partie nord (la zone se soulève) et d’une compression dans la partie sud (la zone s’affaisse). Les taux de rotation sont en moyenne de 0,011°/Ma. Nous avons observé une compression NNO-SSE avec un taux de 3.6 à 8.1 nstrain/an dans la zone sismique du Bas-Saint-Laurent. Dans la zone sismique de Charlevoix, une expansion avec un taux de 3,0 à 7,1 nstrain/an est orientée ENE-OSO. Dans la zone sismique de l’Ouest du Québec, la déformation a un mécanisme de cisaillement avec un taux de compression de 1,0 à 5,1 nstrain/an et un taux d’expansion de 1.6 à 4.1 nstrain/an. Ces mesures sont conformes, au premier ordre, avec les modèles d’ajustement isostatique glaciaire et avec la contrainte de compression horizontale maximale du projet World Stress Map, obtenue à partir de la théorie des mécanismes focaux (focal mechanism method).

Tracking Random Walk of Individual Domain Walls in Cylindrical Nanomagnets with Resistance Noise

The stochasticity of domain-wall (DW) motion in magnetic nanowires has been probed by measuring slow fluctuations, or noise, in electrical resistance at small magnetic fields. By controlled injection of DWs into isolated cylindrical nanowires of nickel, we have been able to track the motion of the DWs between the electrical leads by discrete steps in the resistance. Closer inspection of the time dependence of noise reveals a diffusive random walk of the DWs with a universal kinetic exponent. Our experiments outline a method with which electrical resistance is able to detect the kinetic state of the DWs inside the nanowires, which can be useful in DW-based memory designs.

Novel Evidence hat Attributing Affectively Salient Signal to Random Noise Is Associated with Psychosis

We wished to replicate evidence that an experimental paradigm of speech illusions is associated with psychotic experiences. Fifty-four patients with a first episode of psychosis (FEP) and 150 healthy subjects were examined in an experimental paradigm assessing the presence of speech illusion in neutral white noise. Socio-demographic, cognitive function and family history data were collected. The Positive and Negative Syndrome Scale (PANSS) was administered in the patient group and the Structured Interview for Schizotypy-Revised (SIS-R), and the Community Assessment of Psychic Experiences (CAPE) in the control group. Patients had a much higher rate of speech illusions (33.3% versus 8.7%, ORadjusted: 5.1, 95% CI: 2.3-11.5), which was only partly explained by differences in IQ (ORadjusted: 3.4, 95% CI: 1.4-8.3). Differences were particularly marked for signals in random noise that were perceived as affectively salient (ORadjusted: 9.7, 95% CI: 1.8-53.9). Speech illusion tended to be associated with positive symptoms in patients (ORadjusted: 3.3, 95% CI: 0.9-11.6), particularly affectively salient illusions (ORadjusted: 8.3, 95% CI: 0.7-100.3). In controls, speech illusions were not associated with positive schizotypy (ORadjusted: 1.1, 95% CI: 0.3-3.4) or self-reported psychotic experiences (ORadjusted: 1.4, 95% CI: 0.4-4.6). Experimental paradigms indexing the tendency to detect affectively salient signals in noise may be used to identify liability to psychosis.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Chromatic and luminance losses with multiple sclerosis and optic neuritis measured using dynamic random luminance contrast noise

We measured thresholds for detecting changes in colour and in luminance contrast in observers with multiple sclerosis (MS) and/or optic neuritis (ON) to determine whether reduced sensitivity occurs principally in red-green or blue-yellow second-stage chromatic channels or in an achromatic channel. Colour thresholds for the observers with MS/ON were higher in the red-green direction than in the blue-yellow direction, indicating greater levels of red-green loss than blue-yellow loss. Achromatic thresholds were raised less than either red-green or blue-yellow thresholds, showing less luminance-contrast loss than chromatic loss. With the MS/ON observers, blue-yellow and red-green thresholds were positively correlated but increasing impairment was associated with more rapid changes in red-green thresholds than blue-yellow thresholds. These findings indicate that demyelinating disease selectively reduces sensitivity to colour vision over luminance vision and red-green colours over blue-yellow colours.

Random input problem for the nonlinear Schrödinger equation

We consider the random input problem for a nonlinear system modeled by the integrable one-dimensional self-focusing nonlinear Schrödinger equation (NLSE). We concentrate on the properties obtained from the direct scattering problem associated with the NLSE. We discuss some general issues regarding soliton creation from random input. We also study the averaged spectral density of random quasilinear waves generated in the NLSE channel for two models of the disordered input field profile. The first model is symmetric complex Gaussian white noise and the second one is a real dichotomous (telegraph) process. For the former model, the closed-form expression for the averaged spectral density is obtained, while for the dichotomous real input we present the small noise perturbative expansion for the same quantity. In the case of the dichotomous input, we also obtain the distribution of minimal pulse width required for a soliton generation. The obtained results can be applied to a multitude of problems including random nonlinear Fraunhoffer diffraction, transmission properties of randomly apodized long period Fiber Bragg gratings, and the propagation of incoherent pulses in optical fibers.

Improving visual noise insensitivity in small vocabulary audio visual speech recognition applications

Visual noise insensitivity is important to audio visual speech recognition (AVSR). Visual noise can take on a number of forms such as varying frame rate, occlusion, lighting or speaker variabilities. The use of a high dimensional secondary classifier on the word likelihood scores from both the audio and video modalities is investigated for the purposes of adaptive fusion. Preliminary results are presented demonstrating performance above the catastrophic fusion boundary for our confidence measure irrespective of the type of visual noise presented to it. Our experiments were restricted to small vocabulary applications.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Stability of a Random Diffusion with Linear Drift

We consider a Linear system with Markovian switching which is perturbed by Gaussian type noise, If the linear system is mean square stable then we show that under certain conditions the perturbed system is also stable, We also shaw that under certain conditions the linear system with Markovian switching can be stabilized by such noisy perturbation.

A Nonlinear System Under Combined Periodic and Random Excitation

The anharmonic oscillator under combined sinusoidal and white noise excitation is studied using the Gaussian closure approximation. The mean response and the steady-state variance of the system is obtained by the WKBJ approximation and also by the Fokker Planck equation. The multiple steadystate solutions are obtained and their stability analysis is presented. Numerical results are obtained for a particular set of system parameters. The theoretical results are compared with a digital simulation study to bring out the usefulness of the present approximate theory.

Coalescence of drops in stirred dispersion. A white noise model for coalescence

Coalescence between two droplets in a turbulent liquid-liquid dispersion is generally viewed as a consequence of forces exerted on the drop-pair squeezing out the intervening continuous phase to a critical thickness. A new synthesis is proposed herein which models the film drainage as a stochastic process driven by a suitably idealized random process for the fluctuating force. While the true test of the model lies in detailed parameter estimations with measurement of drop-size distributions in coalescing dispersions, experimental measurements on average coalescence frequencies lend preliminary support to the model.

Learning with symmetric label noise: The importance of being unhinged

Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. This ostensibly shows that convex losses are not SLN-robust. In this paper, we propose a convex, classification-calibrated loss and prove that it is SLN-robust. The loss avoids the Long and Servedio [2008] result by virtue of being negatively unbounded. The loss is a modification of the hinge loss, where one does not clamp at zero; hence, we call it the unhinged loss. We show that the optimal unhinged solution is equivalent to that of a strongly regularised SVM, and is the limiting solution for any convex potential; this implies that strong l2 regularisation makes most standard learners SLN-robust. Experiments confirm the unhinged loss’ SLN-robustness.

Random vibration of a second order non-linear elastic system

A method is presented for obtaining, approximately, the response covariance and probability distribution of a non-linear oscillator under a Gaussian excitation. The method has similarities with the hierarchy closure and the equivalent linearization approaches, but is different. A Gaussianization technique is used to arrive at the output autocorrelation and the input-output cross-correlation. This along with an energy equivalence criterion is used to estimate the response distribution function. The method is applicable in both the transient and steady state response analysis under either stationary or non-stationary excitations. Good comparison has been observed between the predicted and the exact steady state probability distribution of a Duffing oscillator under a white noise input.