TY - GEN
T1 - Gaussian reciprocal sequences from the viewpoint of conditionally Markov sequences
AU - Rezaie, Reza
AU - Rong Li, X.
N1 - Publisher Copyright:
© ACM.
PY - 2018/8/27
Y1 - 2018/8/27
N2 - The conditionally Markov (CM) sequence contains several classes, including the reciprocal sequence. Reciprocal sequences have been widely used in many areas of engineering, including image processing, acausal systems, intelligent systems, and intent inference. In this paper, the reciprocal sequence is studied from the CM sequence point of view, which is different from the viewpoint of the literature and leads to more insight into the reciprocal sequence. Based on this viewpoint, new results, properties, and easily applicable tools are obtained for the reciprocal sequence. The nonsingular Gaussian (NG) reciprocal sequence is modeled and characterized from the CM viewpoint. It is shown that a NG sequence is reciprocal if and only if it is both CML and CMF (two special classes of CM sequences). New dynamic models are presented for the NG reciprocal sequence. These models (unlike the existing one, which is driven by colored noise) are driven by white noise and are easily applicable. As a special reciprocal sequence, the Markov sequence is also discussed. Finally, it can be seen how all CM sequences, including Markov and reciprocal, are unified.
AB - The conditionally Markov (CM) sequence contains several classes, including the reciprocal sequence. Reciprocal sequences have been widely used in many areas of engineering, including image processing, acausal systems, intelligent systems, and intent inference. In this paper, the reciprocal sequence is studied from the CM sequence point of view, which is different from the viewpoint of the literature and leads to more insight into the reciprocal sequence. Based on this viewpoint, new results, properties, and easily applicable tools are obtained for the reciprocal sequence. The nonsingular Gaussian (NG) reciprocal sequence is modeled and characterized from the CM viewpoint. It is shown that a NG sequence is reciprocal if and only if it is both CML and CMF (two special classes of CM sequences). New dynamic models are presented for the NG reciprocal sequence. These models (unlike the existing one, which is driven by colored noise) are driven by white noise and are easily applicable. As a special reciprocal sequence, the Markov sequence is also discussed. Finally, it can be seen how all CM sequences, including Markov and reciprocal, are unified.
KW - Characterization
KW - Conditionally Markov (CM) sequence
KW - Dynamic model
KW - Gaussian sequence
KW - Markov sequence
KW - Reciprocal sequence
UR - https://www.scopus.com/pages/publications/85058635802
U2 - 10.1145/3271553.3271587
DO - 10.1145/3271553.3271587
M3 - 会议稿件
AN - SCOPUS:85058635802
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
PB - Association for Computing Machinery
T2 - 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
Y2 - 27 August 2018 through 29 August 2018
ER -