Manuel Rodriguez-Alvarez

Manuel Rodriguez-Alvarez
University of Granada | UGR · Department of Architecture and Computer Technology

Doctor of Philosophy

About

49
Publications
6,367
Reads
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412
Citations
Citations since 2017
5 Research Items
87 Citations
201720182019202020212022202305101520
201720182019202020212022202305101520
201720182019202020212022202305101520
201720182019202020212022202305101520
Additional affiliations
January 1987 - present
University of Granada
Position
  • Professor (Associate)

Publications

Publications (49)
Article
This article presents the Zynq-embedded node for the Cherenkov telescope array (ZEN-CTA) node, a programmable system-on-chip (SoC) with White Rabbit (WR)-synchronization capability. It targets a solution for the uniform clock and trigger time-stamping module of the small-sized telescopes in the CTA. This module is tasked as a distributed acquisitio...
Article
Our contribution presents a high bandwidth platform that implements traffic aggregation and switching capabilities for the Cherenkov telescope array (CTA) cameras. Our proposed system integrates two different data flows: a unidirectional one from the cameras to an external server and a second one, fully configurable dedicated to configuration and c...
Article
Distributed data acquisition (DAQ) systems are in charge of converting different analog environment signals into digital values to perform control and monitor tasks. They require a computer network technology to share data between their different elements. One of their main issues is to match data with the specific events under study. A possible so...
Conference Paper
Full-text available
A saccade is an ocular movement that is characterized by speed and precision. The velocity profile of this movement is used to extract the maximum speed value, that is one of the most important features of the saccade. A gamma function was used by other authors to describe the waveform shape of the velocity profile. However, this function does not...
Article
Full-text available
As embedded systems are becoming prevalent in everyday life, many universities are incorporating embedded systems-related courses in their undergraduate curricula. However, it is not easy to motivate students in such courses since they conceive of embedded systems as bizarre computing elements, different from the personal computers with which they...
Article
Despite more than 40 years of research, motion estimation is still considered an emerging field, a field especially relevant today because of its vast utility for real-world applications. Currently, even the best bio-inspired algorithms lack certain characteristics that are readily found, for example, naturally in, say, mammals. Furthermore, the va...
Article
Full-text available
Motion estimation from image sequences, called optical flow, has been deeply analyzed by the scientific community. Despite the number of different models and algorithms, none of them covers all problems associated with real-world processing. This paper presents a novel customizable architecture of a neuromorphic robust optical flow (multichannel gr...
Conference Paper
Full-text available
De todas las herramientas de las que dispone el sistema universitario para formar a sus estudiantes, la tutoría es la que presenta una mayor capacidad para dejar una impronta diferenciadora en los alumnos. Por desgracia, en el sistema universitario español esta herramienta tradicionalmente se ha utilizado de manera muy escasa, y normalmente de form...
Conference Paper
The present work describes a reliable improved gradient optical flow estimation system using FPGAs. This structure is based on space-temporal processing and the use of steerable filters. This model can be enhanced using psychophysical and bioinspired properties according to biological vision in order to mimic the singularity and the performance of...
Article
Since the world presents a dynamically changing environment, we need synthetic systems that can process and respond to motion. The main contribution of this work is the efficient implementation of a biologically inspired DSP architecture for gradient motion estimation that borrows nature templates as inspiration and makes use of an specific model o...
Article
Full-text available
The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none o...
Conference Paper
Motion Computation, also called Optical Flow, consists of measuring the motion of an entity attending to the modulus (how fast) and the phase (direction) of its movement. There are a plethora of different models and algorithms whereas none of them cover all problems associated to the real world. Our contribution presents a novel customizable archit...
Chapter
Full-text available
This paper shows an approach to recover original speech signals from their nonlinear mixtures. Using a geometric method that makes a piecewise linear approximation of the nonlinear mixing space, and the fact that the speech distributions are Laplacian or Gamma type, a set of slopes is obtained as a set of linear mixtures.
Conference Paper
Full-text available
Nature has optimized the processing of visual information, especially in primates. The estimation of optical flow is a complex task that gives information about ego-motion, and permits tracking objects from a given scene. The multi-channel spatio-temporal filtering required to detect motion is suitable for a parallel implementation on reconfigurabl...
Article
Full-text available
This paper presents a new adaptive procedure for the linear and nonlinear separation of signals with nonuniform, symmetrical probability distributions, based on both simulated annealing and competitive learning methods by means of a neural network, considering the properties of the vectorial spaces of sources and mixtures, and using a multiple line...
Conference Paper
Full-text available
This paper addresses the characterization of independent and non-Gaussian sources in a linear mixture. We present an eigensystem based approach to determine the number of independent components in the signal received by a single sensor. The temporal structure of the sources is also characterized using fourth-order statistics.
Conference Paper
Full-text available
This paper proposes a novel Independent Component Analysis algorithm based on the use of a genetic algorithm intended for its application to the problem of blind source separation on post-nonlinear mixtures. We present a simple though effective contrast function which evaluates individuals of each population (candidate solutions) based on estimatin...
Conference Paper
Full-text available
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. In this work, the principle...
Conference Paper
Full-text available
This work explains a method for blind separation of a linear mixture of sources, through geometrical considerations concerning the scatter plot. This method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources.
Conference Paper
This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated annealing (SA) and competitive learning (CL) methods by means of a neural network, considering the properties of the vectorial spaces of sources and mixtures, and using a m...
Conference Paper
Full-text available
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. The principles of the new m...
Conference Paper
Full-text available
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. The principles of the new m...
Conference Paper
Blind source separation (BSS) tries to transform a mixed random vector in order to recover the original independent sources. We present a new approach to linear BSS by using either a self-organizing map (SOM) or a neural gas (NG). In comparison to other mixture-space analysis (’geometric’) algorithms, these result in a considerable improvement in s...
Conference Paper
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. In this work, the principle...
Conference Paper
Independent Component Analysis (ICA) is a method for finding underlying factors from multidimensional statistical data. ICA differs from other similar methods in that it looks for components that are both statistically independent and nongaussian. Blind Source Separation (BSS) consists in recovering unobserved signals from a known set of mixtures....
Conference Paper
Full-text available
This work shows a new method for blind separation of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coeflicients of the unknown mixture mafrix A and separates the unknown sources. The principles of the new method and a description...
Conference Paper
Full-text available
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. In this work, the principle...
Article
Full-text available
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. In this work, the principle...
Conference Paper
Full-text available
This paper presents a new adaptive procedure for the linear and nonlinear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated annealing (SA) and competitive learning (CL) methods by means of a neural network, considering the properties of the vectorial spaces of sources and mixtures, and using a mu...
Conference Paper
Various neural network models for the identification and classification of different skin lesions from ALA-induced fluorescence images are presented. After different image preprocessing steps, eigenimages and independent base images are extracted using PCA and ICA, respectively. In order to extract local information in the images rather than global...
Conference Paper
The techniques of Blind Separation of Sources (BSS) are used in many Signal Processing applications in which the data sampled by sensors are a mixture of signals from different sources, and the goal is to obtain an estimation of the sources from the mixtures. This work shows a new method for blind separation of sources, based on geometrical conside...
Article
We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibi...
Conference Paper
This contribution presents a new approach to recover original signals (sources) from their linear mixtures, observed by the same number of sensors. The algorithm proposed assume that the input distributions are bounded and the sources generate certain combinations of boundary values. The method is simpler than other proposals and is based on geomet...
Article
In many Signal Processing applications, data sampled by sensors comprise a mixture of signals from different sources. The problem of separation lies in the reconstruction of sources from the mixtures. In this paper a new method is proposed for the separation of mixed digital sources, based on geometrical considerations, which is applied to the sepa...
Conference Paper
In many Signal Processing applications, data sampled by sensors comprise a mixture of signals from different sources. The problem of separation lies in the reconstruction of sources from the mixtures. In this paper a new method is proposed for the separation of sources, based on geometrical considerations. After a brief introduction, we present the...
Article
Full-text available
This paper presents a new adaptive algorithm for the on- line linear and non-linear separation of signals with non- uniform, symmetrical probability distributions. The procedure is based on the interpretation and properties of the vectorial spaces of sources and mixtures, using a multi ple linearization in the mixture space. The main c haracteristi...
Article
The techniques of Blind Separation of Sources (BSS) are used in many Signal Processing applications in which the data sampled by sensors are a mixture of signals from different sources, and the goal is to obtain an estimation of the sources from the mixtures. This work shows a new method for blind separation of sources, based on geometrical conside...

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