Uniform estimates in the Poincare-Aronszajn theorem on the separation of singularities of analytic functions

We study the possibility of splitting any bounded analytic function $f$ with singularities in a closed set $E\cup F$ as a sum of two bounded analytic functions with singularities in $E$ and $F$ respectively. We obtain some results under geometric restrictions on the sets $E$ and $F$ and we provide some examples showing the sharpness of the positive results.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources

In this article, the fusion of a stochastic metaheuristic as Simulated Annealing (SA) with classical criteria for convergence of Blind Separation of Sources (BSS), is shown. Although the topic of BSS, by means of various techniques, including ICA, PCA, and neural networks, has been amply discussed in the literature, to date the possibility of using simulated annealing algorithms has not been seriously explored. From experimental results, this paper demonstrates the possible benefits offered by SA in combination with high order statistical and mutual information criteria for BSS, such as robustness against local minima and a high degree of flexibility in the energy function.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.