Search results for "pattern"
showing 10 items of 4203 documents
Nonlinear dynamical model of Costas loop and an approach to the analysis of its stability in the large
2015
The analysis of the stability and numerical simulation of Costas loop circuits for high-frequency signals is a challenging task. The problem lies in the fact that it is necessary to simultaneously observe very fast time scale of the input signals and slow time scale of phase difference between the input signals. To overcome this difficult situation it is possible, following the approach presented in the classical works of Gardner and Viterbi, to construct a mathematical model of Costas loop, in which only slow time change of signal?s phases and frequencies is considered. Such a construction, in turn, requires the computation of phase detector characteristic, depending on the waveforms of th…
Pattern formation and spatial correlation induced by the noise in two competing species
2004
We analyze the spatio-temporal patterns of two competing species in the presence of two white noise sources: an additive noise acting on the interaction parameter and a multiplicative noise which affects directly the dynamics of the species densities. We use a coupled map lattice (CML) with uniform initial conditions. We find a nonmonotonic behavior both of the pattern formation and the density correlation as a function of the multiplicative noise intensity.
Nonmonotonic behavior of spatiotemporal pattern formation in a noisy Lotka-Volterra system
2004
The noise-induced pattern formation in a population dynamical model of three interacting species in the coexistence regime is investigated. A coupled map lattice of Lotka-Volterra equations in the presence of multiplicative noise is used to analyze the spatiotemporal evolution. The spatial correlation of the species concentration as a function of time and of the noise intensity is investigated. A nonmonotonic behavior of the area of the patterns as a function of both noise intensity and evolution time is found.
Similarity Solutions and Collapse in the Attractive Gross-Pitaevskii Equation
2000
We analyse a generalised Gross-Pitaevskii equation involving a paraboloidal trap potential in $D$ space dimensions and generalised to a nonlinearity of order $2n+1$. For {\em attractive} coupling constants collapse of the particle density occurs for $Dn\ge 2$ and typically to a $\delta$-function centered at the origin of the trap. By introducing a new dynamical variable for the spherically symmetric solutions we show that all such solutions are self-similar close to the center of the trap. Exact self-similar solutions occur if, and only if, $Dn=2$, and for this case of $Dn=2$ we exhibit an exact but rather special D=1 analytical self-similar solution collapsing to a $\delta$-function which …
Influence of spatial delay on the modulational instability in a composite system with a controllable nonlinearity.
2017
A theoretical investigation of the modulational instability (MI) in a composite system with a nonlocal response function is presented. A composite system of silver nanoparticles in acetone is chosen, whose nonlinearity can be delicately varied by controlling the volume fraction of the constituents, thus enabling the possibility of nonlinearity management. A pump-probe counterpropagation configuration has been assumed, and the interplay between the competing nonlinearities and the nonlocalities in the MI dynamics is systematically explored. A different class of nonlocalities have been considered, and the study reveals that the nonlocality critically depends on the kind of nonlocal function. …
High-order modes in cavity-resonator-integrated guided-mode resonance filters (CRIGFs)
2015
International audience; Cavity-resonator-integrated guided-mode resonance filters (CRIGFs) are optical filters based on weak coupling by a grating between a free-space propagating optical mode and a guided mode, like guided-mode resonance filters (GMRFs). As compared to GMRFs they offer narrowband reflection with small aperture and high angular acceptance. We report experimental characterization and theoretical modeling of unexpected high-order reflected modes in such devices. Using coupled-mode modeling and moiré analysis we provide physical insight on key mechanisms ruling CRIGF properties. This model could serve as a simple and efficient framework to design new reflectors with tailored s…
Conditions for waveguide decoupling in square-lattice photonic crystals
2004
We study coupling and decoupling of parallel waveguides in two-dimensional square-lattice photonic crystals. We show that the waveguide coupling is prohibited at some wavelengths when there is an odd number of rows between the waveguides. In contrast, decoupling does not take place when there is even number of rows between the waveguides. Decoupling can be used to avoid cross talk between adjacent waveguides.
Measuring Spatiotemporal Dependencies in Bivariate Temporal Random Sets with Applications to Cell Biology
2008
Analyzing spatiotemporal dependencies between different types of events is highly relevant to many biological phenomena (e.g., signaling and trafficking), especially as advances in probes and microscopy have facilitated the imaging of dynamic processes in living cells. For many types of events, the segmented areas can overlap spatially and temporally, forming random clumps. In this paper, we model the binary image sequences of two different event types as a realization of a bivariate temporal random set and propose a nonparametric approach to quantify spatial and spatiotemporal interrelations using the pair correlation, cross-covariance, and the Ripley K functions. Based on these summary st…
The impact of feature extraction on the performance of a classifier : kNN, Naïve Bayes and C4.5
2005
"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and the classification error in high dimensions. In this paper, different feature extraction techniques as means of (1) dimensionality reduction, and (2) constructive induction are analyzed with respect to the performance of a classifier. Three commonly used classifiers are taken for the analysis: kNN, Naïve Bayes and C4.5 decision tree. One of the main goals of this paper is to show the importance of the use of class information in feature extraction for classification and (in)appropriateness of random projection or conventional PCA to feature extraction for …
Vector anisotropic filter for multispectral image denoising
2015
In this paper, we propose an approach to extend the application of anisotropic Gaussian filtering for multi- spectral image denoising. We study the case of images corrupted with additive Gaussian noise and use sparse matrix transform for noise covariance matrix estimation. Specifically we show that if an image has a low local variability, we can make the assumption that in the noisy image, the local variability originates from the noise variance only. We apply the proposed approach for the denoising of multispectral images corrupted by noise and compare the proposed method with some existing methods. Results demonstrate an improvement in the denoising performance.