A Study of the Robustness Against SEUs of Digital Circuits Implemented with FPGA DSPs

In this paper we present an experimental validation of the reliability increase of digital circuits implemented in XilinxTMFPGAs when they are implemented using the DSPs (Digital Signal Processors) that are available in the reconfigurable device. For this purpose, we have used a fault-injection platform developed by our research group, NESSY [1]. The presented experiments demonstrate that the probability of occurrence of a SEU effect is similar both in the circuits implemented with and without using embedded DSPs. However, the former are more efficient in terms of area usage, which leads to a decrease in the probability of a SEU occurrence.

Synchronization of Heteroclinic Circuits Through Learning in Chains of Neural Motifs

The synchronization of oscillatory activity in networks of neural networks is usually implemented through coupling the state variables describing neuronal dynamics. In this study we discuss another but complementary mechanism based on a learning process with memory. A driver network motif, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven motif, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner motif can dynamically copy the coupling pattern of the teacher and thus synchronize oscillations with the teacher. Then, we demonstrate that the replication of the WLC dynamics occurs for intermediate memory lengths only. In a unidirectional chain of N motifs coupled through teacher-learner paradigm the time interval required for pattern replication grows linearly with the chain size, hence the learning process does not blow up and at the end we observe phase synchronized oscillations along the chain. We also show that in a learning chain closed into a ring the network motifs come to a consensus, i.e. to a state with the same connectivity pattern corresponding to the mean initial pattern averaged over all network motifs.

Análisis de anomalías gravimétricas y modelación cortical 2D de la región volcánica del Campo de Calatrava (Ciudad Real, España)

La región volcánica de Campo de Calatrava se ha interpretado como un proceso de volcanismo intraplaca desarrollado durante el Neógeno. Se han propuesto dos modelos geodinámicos contrapuestos para explicar el origen de este volcanismo: a) un proceso de rifting en un contexto extensional con un adelgazamiento localizado de corteza; b) un proceso flexural de la litosfera en un contexto compresivo débil sin adelgazamiento de corteza. El análisis de las anomalías gravimétricas de Bouguer y una modelización gravimétrica 2D a escala cortical contribuyen a discriminar entre los modelos geodinámicos propuestos para el origen del volcanismo. Los modelos gravimétricos se han constreñido en base a los estudios sísmicos profundos existentes en la zona y a la cartografía geológica regional. Los modelos gravimétricos descartan un adelgazamiento cortical, lo que cuestiona el modelo de rifting abortado y apoyan la hipótesis alternativa del proceso flexural de la litosfera en régimen compresivo débil como origen del volcanismo bético.