José García Rodríguez

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The dimensionality and complexity of typical multidisciplinary systems hinders the use of formal optimization techniques in application to this class of problems. The use of approximations to represent the system design metrics and constraints has become vital for achieving good performance in many multidisciplinary design optimization (MDO) algorithms.(More)
Infectious bursal disease virus (IBDV) is an avian pathogen responsible for an acute immunosuppressive disease that causes major losses to the poultry industry. Despite having a bipartite dsRNA genome, IBDV, as well as other members of the Birnaviridae family, possesses a single capsid layer formed by trimers of the VP2 capsid protein. The capsid encloses a(More)
Traumatic injury to the adult human spinal cord most frequently occurs at the mid-to-low cervical segments and produces tetraplegia. To investigate treatments for improving upper extremity function after cervical spinal cord injury (SCI), three behavioral tests were examined for their potential usefulness in evaluating forelimb function in an adult rat(More)
In this paper we present a new structure capable of characterizing hand posture, as well as its movement. Topology of a self-organizing neural network determines posture, whereas its adaptation dynamics throughout time determines gesture. This adaptive character of the network allows us to avoid the correspondence problem of other methods, so that the(More)
MR Imaging techniques provide a non-invasive and accurate method for determining the ultra-structural features of human anatomy. In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. Our approach is based on an automated landmark extraction algorithm which automatically selects(More)
This paper aims to address the ability of self-organizing neural network models to manage real-time applications. Specifically, we introduce fAGNG (fast Autonomous Growing Neural Gas), a modified learning algorithm for the incremental model Growing Neural Gas (GNG) network. The Growing Neural Gas network with its attributes of growth, flexibility, rapid(More)
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We propose the use of a self-organizing neural network, the Growing Neural Gas, to represent bidimensional objects, due to its quality of topology preservation. As a result of an adaptative process, the object is represented by a Topology Preserving Graph, that constitutes an induced Delaunay triangulation of their shapes. Features that are extracted from(More)