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Artiicial neural networks achieve fast parallel processing via massively parallel non-linear computational elements. Most neural network models base their ability to adapt to problems on changing the strength of the interconnections between computational elements according to a given learning algorithm. However, constrained interconnection structures may(More)
— If one considers life on Earth since its very beginning , three levels of organization can be distinguished: the phylogenetic level concerns the temporal evolution of the genetic programs within individuals and species, the ontogenetic level concerns the developmental process of a single multicellular organism, and the epigenetic level concerns the(More)
Self-reconfigurable adaptive systems have the possibility of adapting their own hardware configuration. This feature provides enhanced performance and flexibility, reflected in computational cost reductions. Self-reconfigurable adaptation requires powerful optimization algorithms in order to search in a space of possible hardware configurations. If such(More)
In this paper we present a platform for evolving spiking neural networks on FPGAs. Embedded intelligent applications require both high performance, so as to exhibit real-time behavior, and flexibility, to cope with the adaptivity requirements. While hardware solutions offer performance, and software solutions offer flexibility, reconfigurable computing(More)
It is clear to all, after a moments thought, that nature has much we might be inspired by when designing our systems, for example: robustness, adaptability and complexity, to name a few. The implementation of bio-inspired systems in hardware has however been limited, and more often than not been more a matter of artistry than engineering. The reasons for(More)
Randomly connecting networks have proven to be universal computing machines. By interconnecting a set of nodes in a random way one can model very complicated non-linear dynamic systems. Although random Boolean networks (RBN) use Boolean functions as their basic component, there are not hardware implementations of such systems. The absence of implementations(More)
The complexity exhibited by pervasive systems is constantly increasing. Customer electronics devices provide day to day a larger amount of functionalities. A common approach for guaranteeing high performance is to include specialized coprocessor units. However, these systems lack flexibility, since one must define, in advance, the coprocessor functionality.(More)
The CryptoBooster is a modular and reconngurable cryptographic coprocessor that takes full advantage of current high-performance reconngurable circuits (FPGAs) and their partial reconngurability. The CryptoBooster works as a coprocessor with a host system in order to accelerate cryptographic operations. A series of cryptographic modules for diierent(More)