Presenting a single probability-based information-theoretic model for addressing issues in data fusion and sensor management for multi-sensor systems in general and decentralized systems in particular, this text develops mutually consistent data fusion architectures and algorithms. The algorithms are various architectural forms of the information filter and a corresponding Bayesian classification algorithm. Of significance is the normative sensor management method, making use of information-based utility functions.
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Presenting a single probability-based information-theoretic model for addressing issues in data fusion and sensor management for multi-sensor systems in general and decentralized systems in particular, this text develops mutually consistent data fusion architectures and algorithms. The algorithms are various architectural forms of the information filter and a corresponding Bayesian classification algorithm. Of significance is the normative sensor management method, making use of information-based utility functions.
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Add this copy of Data Fusion and Sensor Management: a Decentralized to cart. $92.51, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Santa Clarita, CA, UNITED STATES, published 1994 by Prentice Hall.
