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TIT
2002
125views more  TIT 2002»
13 years 4 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»
13 years 4 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
13 years 7 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
13 years 6 months 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»
13 years 4 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