Search results for "Gaussia"
showing 10 items of 653 documents
Design of dispersion-managed fiber systems for transmitting chirp-free Gaussian pulses
2008
International audience; We present a general method to analytically design a dispersion-managed (DM) fiber system for any desired fiber (dispersion, nonlinearity and losses) and pulse (width and energy) parameters. This analytical design allows one to transmit chirp-free Gaussian pulses (for very long distances) in almost all kinds of DM fiber systems that have appeared so far in the literature, including systems with dispersion map length greater, equal or shorter with respect to the amplification period.
Unifying prospective and retrospective interval-time estimation: A fading-Gaussian activation-based model of interval-timing
2014
International audience; Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies (Block et al., 2010) reveals a striking interaction between the way in which temporal judgments are queried and cognitive load on participants’ judgments of interval duration. For retrospective time judgments, estimates under high cognitive load are longer than under low cognitive load. For prospective judgments, the reverse pattern holds, with increased cognitive load leading to shorter estimates. We describe GAMIT, a Gaussian spreading-activation model,…
Quantitative lower bounds to the Euclidean and the Gaussian Cheeger constants
2020
We provide a quantitative lower bound to the Cheeger constant of a set $\Omega$ in both the Euclidean and the Gaussian settings in terms of suitable asymmetry indexes. We provide examples which show that these quantitative estimates are sharp.
The Joint Censored Gaussian Graphical Lasso Model
2022
The Gaussian graphical model is one of the most used tools for inferring genetic networks. Nowadays, the data are often collected from different sources or under different biological conditions, resulting in heterogeneous datasets that exhibit a dependency structure that varies across groups. The complex structure of these data is typically recovered using regularized inferential procedures that use two penalties, one that encourages sparsity within each graph and the other that encourages common structures among the different groups. To this date, these approaches have not been developed for handling the case of censored data. However, these data are often generated by gene expression tech…
Robust Light Field Watermarking by 4D Wavelet Transform
2020
Unlike common 2D images, the light field representation of a scene delivers spatial and angular description which is of paramount importance for 3D reconstruction. Despite the numerous methods proposed for 2D image watermarking, such methods do not address the angular information of the light field. Hence the exploitation of such methods may cause severe destruction of the angular information. In this paper, we propose a novel method for light field watermarking with extensive consideration of the spatial and angular information. Considering the 4D innate of the light field, the proposed method incorporates 4D wavelet for the purpose of watermarking and converts the heavily-correlated chann…
On the analysis of the cat's pattern recognition system
1983
The objective of the paper is to determine in abstract terms the algorithms used by the cat detecting simple patterns and to quantify the contributions of the visual areas 17, 18, 19 for this task. The data incorporated in the algorithm are collected from behavioral experiments where the animals had to distinguish between two patterns. The patterns were superimposed with gaussian noise and the detection probability was measured. The resulting model describes pattern recognition in two steps: first extraction of features and second classification. The test of the validity of the model system was to predict the outcome of similar experiments but with different patterns. With the help of the m…
Introducing ARTMO's Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape.
2022
Accurate plant-type (PT) detection forms an important basis for sustainable land management maintaining biodiversity and ecosystem services. In this sense, Sentinel-2 satellite images of the Copernicus program offer spatial, spectral, temporal, and radiometric characteristics with great potential for mapping and monitoring PTs. In addition, the selection of a best-performing algorithm needs to be considered for obtaining PT classification as accurate as possible . To date, no freely downloadable toolbox exists that brings the diversity of the latest supervised machine-learning classification algorithms (MLCAs) together into a single intuitive user-friendly graphical user interface (GUI). To…
Order statistics-based parametric classification for multi-dimensional distributions
2013
Traditionally, in the field of Pattern Recognition (PR), the moments of the class-conditional densities of the respective classes have been used to perform classification. However, the use of phenomena that utilized the properties of the Order Statistics (OS) were not reported. Recently, in [10,8], we proposed a new paradigm named CMOS, Classification by the Moments of Order Statistics, which specifically used these quantifiers. It is fascinating that CMOS is essentially ''anti''-Bayesian in its nature because the classification is performed in a counter-intuitive manner, i.e., by comparing the testing sample to a few samples distant from the mean, as opposed to the Bayesian approach in whi…
Recovery of time-dependent coefficients from boundary data for hyperbolic equations
2019
We study uniqueness of the recovery of a time-dependent magnetic vector-valued potential and an electric scalar-valued potential on a Riemannian manifold from the knowledge of the Dirichlet to Neumann map of a hyperbolic equation. The Cauchy data is observed on time-like parts of the space-time boundary and uniqueness is proved up to the natural gauge for the problem. The proof is based on Gaussian beams and inversion of the light ray transform on Lorentzian manifolds under the assumptions that the Lorentzian manifold is a product of a Riemannian manifold with a time interval and that the geodesic ray transform is invertible on the Riemannian manifold.
Stochastic dynamical modelling of spot freight rates
2014
Based on empirical analysis of the Capesize and Panamax indices, we propose different continuous-time stochastic processes to model their dynamics. The models go beyond the standard geometric Brownian motion, and incorporate observed effects like heavy-tailed returns, stochastic volatility and memory. In particular, we suggest stochastic dynamics based on exponential Levy processes with normal inverse Gaussian distributed logarithmic returns. The Barndorff-Nielsen and Shephard stochastic volatility model is shown to capture time-varying volatility in the data. Finally, continuous-time autoregressive processes provide a class of models sufficiently rich to incorporate short-term persistence …