Depuis son introduction en 1982, la carte auto-organisatrice de Kohonen (Self-Organizing Map : SOM) a prouvé ses capacités de classification et visualisation des données multidimensionnelles dans différents domaines d’application. Les implémentations matérielles de la carte SOM, en exploitant le taux de parallélisme élevé de l’algorithme de Kohonen, permettent d’augmenter les performances de ce modèle neuronal souvent au détriment de la flexibilité. D’autre part, la flexibilité est offerte par les implémentations logicielles qui quant à elles ne sont pas adaptées pour les applications temps réel à cause de leurs performances temporelles limitées. Dans cette thèse nous avons proposé une architecture matérielle distribuée, adaptable, flexible et extensible de la carte SOM à base de NoC dédiée pour une implantation matérielle sur FPGA. A base de cette approche, nous avons également proposé une architecture matérielle innovante d’une carte SOM à structure croissante au cours de la phase d’apprentissage / Since its introduction in 1982, Kohonen’s Self-Organizing Map (SOM) showed its ability to classify and visualize multidimensional data in various application fields. Hardware implementations of SOM, by exploiting the inherent parallelism of the Kohonen algorithm, allow to increase the overall performances of this neuronal network, often at the expense of the flexibility. On the other hand, the flexibility is offered by software implementations which on their side are not suited for real-time applications due to the limited time performances. In this thesis we proposed a distributed, adaptable, flexible and scalable hardware architecture of SOM based on Network-on-Chip (NoC) designed for FPGA implementation. Moreover, based on this approach we also proposed a novel hardware architecture of a growing SOM able to evolve its own structure during the learning phase

Made available in DSpace on 2014-12-17T14:08:50Z (GMT). No. of bitstreams: 1 PauloRMP_capa_ate_pag32.pdf: 5057325 bytes, checksum: bf8da0b02ad06ee116c93344fb67e976 (MD5) Previous issue date: 2012-02-06 / Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization / Originalmente voltadas ao monitoramento da opera??o, as medi??es cont?nuas de press?o e temperatura no fundo de po?o, realizadas atrav?s de PDGs (do ingl?s, Permanent Downhole Gauges), encontram vasta aplicabilidade no gerenciamento de reservat?rios. Para tanto, permitem o monitoramento do desempenho de po?os e a estimativa de par?metros de reservat?rios no longo prazo. Contudo, a despeito de sua inquestion?vel utilidade, os dados adquiridos de PDG apresentam grande conte?do de ru?do. Outro aspecto igualmente desfavor?vel reside na ocorr?ncia de valores esp?rios (outliers) imersos entre as medidas registradas pelo PDG. O presente trabalho aborda o tratamento inicial de sinais de press?o e temperatura, mediante t?cnicas de suaviza??o, mapas auto-organiz?veis e transformada wavelet discreta. Ademais, prop?e-se um sistema de detec??o de transientes relevantes para an?lise no longo hist?rico de registros, baseado no acoplamento entre clusteriza??o fuzzy e redes neurais feed-forward. Os resultados alcan?ados mostraram-se de todo satisfat?rios para po?os marinhos, atendendo a requisitos reais de utiliza??o dos sinais registrados por PDGs