Greedy Reduction Algorithms for Mixtures of Exponential Family

Ardeshiri T., Granstrom K., Ozkan E., ORGUNER U.

IEEE SIGNAL PROCESSING LETTERS, cilt.22, sa.6, ss.676-680, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 6
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1109/lsp.2014.2367154
  • Dergi Adı: IEEE SIGNAL PROCESSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.676-680
  • Anahtar Kelimeler: Exponential family, extended target, integral square error, Kullback-Leibler divergence, mixture density, mixture reduction, target tracking, RANDOM MATRICES, TRACKING, FILTER
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this letter, we propose a general framework for greedy reduction of mixture densities of exponential family. The performances of the generalized algorithms are illustrated both on an artificial example where randomly generated mixture densities are reduced and on a target tracking scenario where the reduction is carried out in the recursion of a Gaussian inverse Wishart probability hypothesis density (PHD) filter.