Identification of bilinear forms with the kalman filter

Laura Maria Dogariu , Silviu Ciochina (1) , Constantin Paleologu (1) , Jacob Benesty (2) , Pablo Piantanida (3)

1 UPB - University Politehnica of Bucharest [Romania]
2 INRS - Institut National de la Recherche Scientifique [Québec]
3 L2S - Laboratoire des signaux et systèmes

In this paper, we develop the Kalman filter for the identification of bilinear forms. In this framework, the bilinear term is defined with respect to the impulse responses of a spatiotemporal model, which resembles a multiple-input/single-output system. Recently, the identification of such bilinear forms was addressed in terms of the Wiener filter and conventional adaptive algorithms, i.e., least-mean-square and recursive least-squares. In this work, apart from the derivation of the Kalman filter tailored for the identification of bilinear forms, a simplified (i.e., low complexity) version of the algorithm is also presented. Simulation results support the theoretical findings and indicate the good performance of the proposed solutions.

Domains: Information Theory [cs.IT]; Networking and Internet Architecture [cs.NI]; Information Theory [math.IT]; Statistics [math.ST]

Laura Maria Dogariu, Silviu Ciochina, Constantin Paleologu, Jacob Benesty, Pablo Piantanida. Identification of bilinear forms with the kalman filter. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Apr 2018, Calgary, Canada. ⟨10.1109/icassp.2018.8461971⟩. ⟨hal-01742448⟩