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Description

Autonomous systems require reasoning and decision-making capabilities in real time. In order to comply with these timing requirements, computing tasks have to be performed as fast as possible. The problem arises when computations are no longer simple, but very time-consuming operations. A good example can be found in autonomous navigation systems with visual-tracking submodules where Kalman filtering is the most extended solution. However, in recent years, some interesting new approaches have been developed. Particle filtering, given its more general problem-solving features, has reached an important position in the field. Traditional approaches to particle filtering or evolutionary computation have been developed in software platforms, including parallel capabilities to some extent. In this work, an additional goal is fully exploiting hardware implementation advantages. By using the computational resources available in a FPGA device, better performance results in terms of computation time are expected. These hardware resources will be in charge of extensive repetitive computations. With this hardware-based implementation, real-time features are also expected.

Contributeurs

Auteur Alfonso Rodríguez

Auteur Félix Moreno

Détails sur le produit

DUIN 3FMI1Q0D9N7

GTIN 9783659616655

Langue Anglais

Nombre de pages 120

Type de produit Livre de Poche

Dimension 220 x 150 x 6  mm

Poids du produit 176 g

Hardware-Based Particle Filter with Evolutionary Resampling Stage

Alfonso Rodríguez

39,32 €

Vendeur: Dodax EU

Date de livraison: entre mardi, 24. septembre et jeudi, 26. septembre

État: Neuf

TVA incluse - Livraison GRATUITE
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39,32 €
TVA incluse - Livraison GRATUITE