Conference proceeding
Simple local partition rules in multi-bit decision fusion
Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems
1994
Abstract
A parallel decision fusion system is studied where local detectors (LDs) collect information about a binary hypothesis, and transmit multi-bit intermediate decisions to a data fusion center (DFC). The DFC compresses the local decisions into a final binary decision. The objective function is the Bayesian risk. Equations for the optimal decision rules for the LDs and the DFC have been derived by Lee-Chao (1989), but the computational complexity of solving them is formidable. To address this difficulty, we propose several suboptimal LD-design schemes. For each one we design a DFC, which is optimally conditioned on the fixed LD rules. We calculate the exact performance of each scheme, thus providing a means for selection of the most appropriate one under given observation conditions. We demonstrate performance for two important binary decision tasks: discrimination between two Gaussian hypotheses of equal variances and different means; and discrimination between two Gaussian hypotheses of equal means and different variances.< >
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Details
- Title
- Simple local partition rules in multi-bit decision fusion
- Creators
- M Kam - Drexel UniversityXiaoxun Zhu - Drexel UniversityIEEE
- Publication Details
- Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Web of Science ID
- WOS:A1994BD66G00028
- Other Identifier
- 991019346796504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Instruments & Instrumentation
- Mathematics, Applied
- Remote Sensing