Proceedings ArticleDOI
Sequential detection with limited memory
Emre Ertin,Lee C. Potter +1 more
- pp 585-588
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TLDR
In this article, the design of sequential detection tests under memory constraints is studied and the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory is derived.Abstract:
Sequential tests outperform fixed sample size tests by requiring fewer samples on average to achieve the same level of error performance The sequential probability ratio test (SPRT) has been suggested by Wald (1947) for sequential binary hypothesis testing problems SPRT recursively calculates the likelihood of an observed data stream and requires this likelihood to be stored in memory between samples In this paper we study the design of sequential detection tests under memory constraints We derive the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory An application of the proposed techniques is large scale sensor networks where price and communication constraints dictate limited complexity devices, which store and transmit concise representations of the state of natureread more
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References
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