Search results for "signal processing"
showing 10 items of 2451 documents
Optimal band selection for future satellite sensor dedicated to soil science
2009
Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce …
Transitions between imperfectly ordered crystalline structures: A phase switch Monte Carlo study
2012
A model for two-dimensional colloids confined laterally by ``structured boundaries'' (i.e., ones that impose a periodicity along the slit) is studied by Monte Carlo simulations. When the distance $D$ between the confining walls is reduced at constant particle number from an initial value ${D}_{0}$, for which a crystalline structure commensurate with the imposed periodicity fits, to smaller values, a succession of phase transitions to imperfectly ordered structures occur. These structures have a reduced number of rows parallel to the boundaries (from $n$ to $n\ensuremath{-}1$ to $n\ensuremath{-}2$, etc.) and are accompanied by an almost periodic strain pattern, due to ``soliton staircases'' …
Sub-threshold signal processing in arrays of non-identical nanostructures
2011
Weak input signals are routinely processed by molecular-scaled biological networks composed of non-identical units that operate correctly in a noisy environment. In order to show that artificial nanostructures can mimic this behavior, we explore theoretically noise-assisted signal processing in arrays of metallic nanoparticles functionalized with organic ligands that act as tunneling junctions connecting the nanoparticle to the external electrodes. The electronic transfer through the nanostructure is based on the Coulomb blockade and tunneling effects. Because of the fabrication uncertainties, these nanostructures are expected to show a high variability in their physical characteristics and…
Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp
2017
Blind source separation (BSS) is a well-known signal processing tool which is used to solve practical data analysis problems in various fields of science. In BSS, we assume that the observed data consists of linear mixtures of latent variables. The mixing system and the distributions of the latent variables are unknown. The aim is to find an estimate of an unmixing matrix which then transforms the observed data back to latent sources. In this paper we present the R packages JADE and BSSasymp. The package JADE offers several BSS methods which are based on joint diagonalization. Package BSSasymp contains functions for computing the asymptotic covariance matrices as well as their data-based es…
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002
2007
Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …
Multiscale Granger causality
2017
In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well-established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer a…
Forward likelihood-based predictive approach for space-time point processes
2011
Dealing with data from a space–time point process, the estimation of the conditional intensity function is a crucial issue even if a complete definition of a parametric model is not available. In particular, in case of exploratory contexts or if we want to assess the adequacy of a specific parametric model, some kind of nonparametric estimation procedure could be useful. Often, for these purposes kernel estimators are used and the estimation of the intensity function depends on the estimation of bandwidth parameters. In some fields, like for instance the seismological one, predictive properties of the estimated intensity function are pursued. Since a direct ML approach cannot be used, we pr…
Investigation of acceptance simulated annealing — A simplified approach to adaptive cooling schedules
2010
Abstract Simulated annealing is the classic physical optimization algorithm, which has been applied to a large variety of problems for many years. Over time, several adaptive mechanisms for decreasing the temperature and thus controlling the acceptance of deteriorations have been developed, based on the measurement of the mean value and the variance of the energy. Here we propose a new simplified approach in which we consider the probability of accepting deteriorations as the main control parameter and derive the temperature by averaging over the last few deteriorations stored in a memory. We present results for the traveling salesman problem and demonstrate, how the amount of data retained…
Tuning active Brownian motion with shot noise energy pulses
2009
The main aim of this work is to explore the possibility of modeling the biological energy support mediated by absorption of ATP (adenosine triphosphate) as an energetic shot noise. We develop a general model with discrete input of energy pulses and study shot-noise-driven ratchets. We consider these ratchets as prototypes of Brownian motors driven by energy-rich ATP molecules. Our model is a stochastic machine able to acquire energy from the environment and convert it into kinetic energy of motion. We present characteristic features and demonstrate the possibility of tuning these motors by adapting the mean frequency of the discrete energy inputs, which are described as a special shot noise…
High-Temperature Series Analysis of the Free Energy and Susceptibility of the 2D Random-Bond Ising Model
1999
We derive high-temperature series expansions for the free energy and susceptibility of the two-dimensional random-bond Ising model with a symmetric bimodal distribution of two positive coupling strengths J_1 and J_2 and study the influence of the quenched, random bond-disorder on the critical behavior of the model. By analysing the series expansions over a wide range of coupling ratios J_2/J_1, covering the crossover from weak to strong disorder, we obtain for the susceptibility with two different methods compelling evidence for a singularity of the form $\chi \sim t^{-7/4} |\ln t|^{7/8}$, as predicted theoretically by Shalaev, Shankar, and Ludwig. For the specific heat our results are less…