Approximation of Basic Belief Assignment Based on Focal Element Compatibility

Approximation d'une assignation basique de croyance par compatibilité des éléments focaux

Qing Wei (1) , Xinde Li (1) , Jean Dezert (2)

1 NJUST - School of Automation [Nanjing]
2 DTIS, ONERA, Université Paris Saclay (COmUE) [Palaiseau]

The theory of belief functions is an important tool in the field of information fusion. However, the fusion of Basic Belief Assignments (BBAs) requires high computational cost and long computing time when a large number of focal elements are involved in the fusion rules. This problem becomes a bottleneck of application of Belief Functions (BF) in high-dimensional real problems. To overcome this drawback, many approaches were proposed to approximate BBAs to reduce the computational complexity in the fusion process. In this paper, we present a novel method based on the compatibility of focal elements to approximate a BBA by removing some focal elements of the original BBA. Besides, a new mass assignment strategy based on the distance of focal elements is proposed. Several examples, simulations and related analyses are provided to illustrate the interest and efficiency of the proposed method.

Mots clés: INFORMATION FUSION; BELIEF FUNCTIONS; BASIC BELIEF ASSIGNMENT; APPROXIMATION

Mots clés: FUSION D'INFORMATION; FONCTIONS DE CROYANCE; ASSIGNATION BASIQUE DE CROYANCE

Domaines: Sciences de l'ingénieur [physics]; Physique [physics]; Mathématiques [math]; Informatique [cs]

Qing Wei, Xinde Li, Jean Dezert. Approximation of Basic Belief Assignment Based on Focal Element Compatibility. FUSION 2019, Jul 2019, OTTAWA, Canada. ⟨hal-02355654⟩