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TIT
2002
125views more  TIT 2002»
14 years 11 months ago
Optimal bi-level quantization of i.i.d. sensor observations for binary hypothesis testing
We consider the problem of binary hypothesis testing using binary decisions from independent and identically distributed (i.i.d). sensors. Identical likelihood-ratio quantizers wit...
Qian Zhang, Pramod K. Varshney, Richard D. Wesel
JCM
2006
118views more  JCM 2006»
14 years 11 months ago
Joint Optimization of Local and Fusion Rules in a Decentralized Sensor Network
Decentralized sensor networks are collections of individual local sensors that observe a common phenomenon, quantize their observations, and send this quantized information to a ce...
Nithya Gnanapandithan, Balasubramaniam Natarajan
AAAI
2007
15 years 1 months ago
Filtering, Decomposition and Search Space Reduction for Optimal Sequential Planning
We present in this paper a hybrid planning system which combines constraint satisfaction techniques and planning heuristics to produce optimal sequential plans. It integrates its ...
Stéphane Grandcolas, C. Pain-Barre
NIPS
2007
15 years 29 days ago
Sequential Hypothesis Testing under Stochastic Deadlines
Most models of decision-making in neuroscience assume an infinite horizon, which yields an optimal solution that integrates evidence up to a fixed decision threshold; however, u...
Peter Frazier, Angela Yu
CORR
2007
Springer
131views Education» more  CORR 2007»
14 years 11 months ago
Bayesian sequential change diagnosis
Sequential change diagnosis is the joint problem of detection and identification of a sudden and unobservable change in the distribution of a random sequence. In this problem, the...
Savas Dayanik, Christian Goulding, H. Vincent Poor