A Deterministic Annealing PMHT Algorithm with an Application to Particle Tracking

A scenario generator is said to manifest in-sample stability if, when generating several scenario sets of the same size and solving the optimisation problem on each of these

In order to incorporate asynchronous communications in the algorithm, the idea is to reformulate the second sum in (1) as an expectation over the (random) active edges and then to

In our video tracking framework, when new moving objects are added in the scene, more prototypes are needed to keep the same accuracy of the vector quantization (i.e. to keep

To sum up, there is no doubt that application the second fitness function gives us better results but if we compare Cuckoo Search Algorithm and Simulated Annealing it turns out that

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Finally, we conclude the paper by proposing a potential use of the synchrosqueezing method to determine a relevant sampling strategy for multicomponent signals analysis and also

In this paper, we proposed a new tracking framework based on Particle Swarm Optimization formalism and, demonstrated on both, synthetic and real data, that our algorithm outper-

A typical algorithm that was known to perform well in the case of time-cheap cost evaluations was the simulated annealing (SA) as mentioned by Locatelli in [19]: ”The latter