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Combinatorial structures and filter ...

Yu, Jingjin.

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Combinatorial structures and filter design in information spaces.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Combinatorial structures and filter design in information spaces./
作者:	Yu, Jingjin.
面頁冊數:	143 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
Contained By:	Dissertation Abstracts International75-03B(E).
標題:	Engineering, Robotics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3603721
ISBN:	9781303584756

Combinatorial structures and filter design in information spaces.
Yu, Jingjin.

Combinatorial structures and filter design in information spaces. - 143 p.

Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2013.

In this thesis, we develop a filtering process called combinatorial filters for handling combinatorial processes that evolve over time and study two practical problems using this method.

ISBN: 9781303584756Subjects--Topical Terms:

1018454
Engineering, Robotics.

Combinatorial structures and filter design in information spaces.
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245 1 0 $a Combinatorial structures and filter design in information spaces.
300 $a 143 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
500 $a Adviser: Steven M. LaValle.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2013.
520 $a In this thesis, we develop a filtering process called combinatorial filters for handling combinatorial processes that evolve over time and study two practical problems using this method.
520 $a The first problem is a generalization of the sensing aspect of visibility-based pursuit evasion games, in which the task is to maintain the distribution of hidden targets that move outside the field of view while a sensor sweep is being performed. For this problem, we apply information space concepts to significantly reduce the general complexity so that information is processed only when the shadow region (all points invisible to the sensors) changes combinatorially or targets pass in and out of the field of view. The cases of distinguishable, partially distinguishable, and completely indistinguishable targets are handled. Depending on whether the targets move nondeterministically or probabilistically, more specific classes of problems are formulated. For each case, efficient filtering algorithms are introduced, implemented, and demonstrated that provide critical information for tasks such as counting, herding, pursuit-evasion, and situational awareness.
520 $a Next, we study the problem of using sparse, heterogeneous sensor data to verify the stories (i.e., path samples) of agents. Since there are two sets of data, the combinatorial filter for this problem can be built in two ways: Using a filter (an automaton) built from sensor data to process the story or using a filter built from the story to process the sensor data. Both approaches lead to dynamic programming based efficient algorithms for extracting a compatible path if one exists. In addition to exact path inference, our method also applies to approximate path inference that allows errors in data. Besides immediate applicability toward security and forensics problems, the idea of behavior validation using external sensors also appears promising in complementing design time model verification.
590 $a School code: 0090.
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
710 2 $a University of Illinois at Urbana-Champaign. $b Electrical & Computer Eng. $3 2096322
773 0 $t Dissertation Abstracts International $g 75-03B(E).
790 $a 0090
791 $a Ph.D.
792 $a 2013
793 $a English
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