Motivated by the work of Grujić and Kalisch, [Z. Grujić and H. Kalisch, Local well-posedness of the generalized Korteweg-de Vries equation in spaces of analytic functions, Differential and Integral Equations 15 (2002) 1325–1334], we prove the local well-posedness for the periodic KdV equation in spaces of periodic functions analytic on a strip around the real axis without shrinking the width of...

Data acquisition technologies can provide large datasets with millions of samples for statistical analysis. This creates a tremendous challenge for pattern recognition techniques, which need to be more efficient without loosing their effectiveness. We have tried to circumvent the problem by reducing it into the fast computation of an optimum-path forest (OPF) in a graph derived from the trainin...

AbsCrocr-Robotic manipulators wiU play a significant role in the maintenance and repair of space stations and satellites, and other f u m space missions. Robot path planning and control for the above applications should be optimum, since any inetedency in the planning may considerably risk the success of the space mission. This paper prrsents a global optimum path planning scheme for redundant ...

Path cost optimization is essential for maneuvering vehicles in a cost effective way. The term cost can be interpreted as fuel consumption, path visibility, probability of being detected, probability of being attacked or a combination of the above. Exact algorithms such as linear programming and dynamic programming can always provide globally optimum solution to such a problem. However, as the ...

As the migration of wireless communication network from one generation to another continue, radio wave propagation model or path loss model plays a very significant role in achieving an optimum performance as well as suitability over different locations of interest. In this research, investigation of radio communication channel behavior based on practical measurement in the L-band frequency in ...

We present an approach for supervised classification, which interprets a training set as a complete graph, identifies prototypes in all classes, and computes an optimum-path forest rooted at them. The class of a sample in a tree is assumed to be the same of its root. A test sample is classified by identifying which tree would contain it. We show how to improve performance from the errors on an ...

Probabilistic-driven classification techniques extend the role of traditional approaches that output labels (usually integer numbers) only. Such techniques are more fruitful when dealing with problems where one is not interested in recognition/identification only, but also into monitoring the behavior of consumers and/or machines, for instance. Therefore, by means of probability estimates, one ...