A Joint Optimization Criterion for Blind DS-CDMA Detection

This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by Tugnait and Li in 2001, we propose to tackle the problem in the context of the blind signal extraction methods for ICA. In order to improve the performance of the detector, we present a criterion based on the joint optimization of several higher-order statistics of the outputs. An algorithm that optimizes the proposed criterion is described, and its improved performance and robustness with respect to the near-far problem are corroborated through simulations. Additionally, a simulation using measurements on a real software-radio platform at 5 GHz has also been performed.Ministerio de Ciencia y tecnología TEC2004-06451-C05-0

Determinantes de la estructura de capital de los establecimientos de crédito en Colombia: 1992-2003

El propósito de este artículo es analizar qué factores determinan la estructura de capital de los establecimientos de crédito en Colombia. Con este fin se hace una revisión de la literatura existente en torno al tema y, asumiendo que se cumple la hipótesis propuesta en algunas teorías de que existe una estructura de capital óptima, se implementa un modelo de optimización de un establecimiento de crédito representativo para observar cómo afectan estos factores a dicha estructura de capital óptima. Adicionalmente, se corre un modelo de panel de datos dinámico para contrastar los resultados teóricos con la evidencia empírica para los establecimientos de crédito colombianos. Finalmente se postulan algunas conclusiones sobre los resultados encontrado

Determinantes de la estructura de capital de los establecimientos de crédito en Colombia: 1992-2003

El propósito de este artículo es analizar qué factores determinan la estructura de capital de los establecimientos de crédito en Colombia. Con este fin se hace una revisión de la literatura existente en torno al tema y, asumiendo que se cumple la hipótesis propuesta en algunas teorías de que existe una estructura de capital óptima, se implementa un modelo de optimización de un establecimiento de crédito representativo para observar cómo afectan estos factores a dicha estructura de capital óptima. Adicionalmente, se corre un modelo de panel de datos dinámico para contrastar los resultados teóricos con la evidencia empírica para los establecimientos de crédito colombianos. Finalmente se postulan algunas conclusiones sobre los resultados encontrado

Efectos macroeconómicos asociados a cambios en la tasa marginal impositiva

In this paper is analyzed the macroeconomic effects associated with increases in the capital tax rate and labor tax rate under a Neoclassical model with elastic labor supply and positive externalities due to government's spending. It is found that these policies reduce the production, the investment and the labor supply; however, the effects over the consumption are different. It is concluded that tax reforms based on labor income is more contractive that tax reforms based on capital income.Tasa marginal impositiva, modelos estocásticos, simulación

Centroid-Based Clustering with ab-Divergences

Centroid-based clustering is a widely used technique within unsupervised learning algorithms in many research fields. The success of any centroid-based clustering relies on the choice of the similarity measure under use. In recent years, most studies focused on including several divergence measures in the traditional hard k-means algorithm. In this article, we consider the problem of centroid-based clustering using the family of ab-divergences, which is governed by two parameters, a and b. We propose a new iterative algorithm, ab-k-means, giving closed-form solutions for the computation of the sided centroids. The algorithm can be fine-tuned by means of this pair of values, yielding a wide range of the most frequently used divergences. Moreover, it is guaranteed to converge to local minima for a wide range of values of the pair (a, b). Our theoretical contribution has been validated by several experiments performed with synthetic and real data and exploring the (a, b) plane. The numerical results obtained confirm the quality of the algorithm and its suitability to be used in several practical applications.MINECO TEC2017-82807-

Initialization method for speech separation algorithms that work in the time-frequency domain

This article addresses the problem of the unsupervised separa tion of speech signals in realistic scenarios. An initialization procedure is proposed for independent component analysis (ICA) algorithms that work in the time-frequency domain and require the prewhitening of the observations. It is shown that the proposed method drastically reduces the permuted solu tions in that domain and helps to reduce the execution time of the algorithms. Simulations confirm these advantages for several ICA instantaneous algo rithms and the effectiveness of the proposed technique in emulated reverber ant environments.Ministerio de Ciencia y tecnología (España) TEC2008-0625

Trace-based cryptoanalysis of cyclotomic Rq,0×RqR_{q,0}\times R_q-PLWE for the non-split case

We describe a decisional attack against a version of the PLWE problem in which the samples are taken from a certain proper subring of large dimension of the cyclotomic ring $\mathbb{F}_q[x]/(\Phi_{p^k}(x))$ with $k>1$ in the case where $q\equiv 1\pmod{p}$ but $\Phi_{p^k}(x)$ is not totally split over $\mathbb{F}_q$. Our attack uses the fact that the roots of $\Phi_{p^k}(x)$ over suitable extensions of $\mathbb{F}_q$ have zero-trace and has overwhelming success probability as a function of the number of input samples. An implementation in Maple and some examples of our attack are also provided.Comment: 19 pages; 1 figure; Major update to previous version due to some weaknesses detecte

A Method for Unsupervised Semi-Quantification of Inmunohistochemical Staining with Beta Divergences

In many research laboratories, it is essential to determine the relative expression levels of some proteins of interest in tissue samples. The semi-quantitative scoring of a set of images consists of establishing a scale of scores ranging from zero or one to a maximum number set by the researcher and assigning a score to each image that should represent some predefined characteristic of the IHC staining, such as its intensity. However, manual scoring depends on the judgment of an observer and therefore exposes the assessment to a certain level of bias. In this work, we present a fully automatic and unsupervised method for comparative biomarker quantification in histopathological brightfield images. The method relies on a color separation method that discriminates between two chromogens expressed as brown and blue colors robustly, independent of color variation or biomarker expression level. For this purpose, we have adopted a two-stage stain separation approach in the optical density space. First, a preliminary separation is performed using a deconvolution method in which the color vectors of the stains are determined after an eigendecomposition of the data. Then, we adjust the separation using the non-negative matrix factorization method with beta divergences, initializing the algorithm with the matrices resulting from the previous step. After that, a feature vector of each image based on the intensity of the two chromogens is determined. Finally, the images are annotated using a systematically initialized k-means clustering algorithm with beta divergences. The method clearly defines the initial boundaries of the categories, although some flexibility is added. Experiments for the semi-quantitative scoring of images in five categories have been carried out by comparing the results with the scores of four expert researchers yielding accuracies that range between 76.60% and 94.58%. These results show that the proposed automatic scoring system, which is definable and reproducible, produces consistent results.FEDER / Junta de Andalucía-Consejería de Economía y Conocimiento US-1264994Fondo de Desarrollo (FEDER). Unión Europea PGC2018-096244-B-I00, SAF2016-75442-RMinisterio de Economía, Industria y Competitividad (MINECO). España TEC2017- 82807-

Centroid-Based Clustering with αβ-Divergences

Article number 196Centroid-based clustering is a widely used technique within unsupervised learning algorithms in many research fields. The success of any centroid-based clustering relies on the choice of the similarity measure under use. In recent years, most studies focused on including several divergence measures in the traditional hard k-means algorithm. In this article, we consider the problem of centroid-based clustering using the family of αβ-divergences, which is governed by two parameters, α and β. We propose a new iterative algorithm, αβ-k-means, giving closed-form solutions for the computation of the sided centroids. The algorithm can be fine-tuned by means of this pair of values, yielding a wide range of the most frequently used divergences. Moreover, it is guaranteed to converge to local minima for a wide range of values of the pair (α, β). Our theoretical contribution has been validated by several experiments performed with synthetic and real data and exploring the (α, β) plane. The numerical results obtained confirm the quality of the algorithm and its suitability to be used in several practical applicationsMinisterio de Economía y Competitividad de España (MINECO) TEC2017-82807-

Solving permutations in frequencyy-domain for blind separation of an arbitrary number of speech sources

Blind separation of speech sources in reverberant environ ments is usually performed in the time-frequency domain, which gives rise to the permutation problem: the different ordering of estimated sources for different frequency components. A two-stage method to solve permutations with an arbitrary number of sources is proposed. The suggested procedure is based on the spectral consistency of the sources. At the first stage frequency bins are compared with each other, while at the second stage the neighboring frequencies are emphasized. Experiments for perfect separation situations and for live recordings show that the proposed method improves the results of existing approaches.Ministerio de Ciencia e Innovación (España) TEC2011-2355