Title :
Minimax robust decentralized detection
Author :
Veeravalli, Venugopal V. ; Basar, Tamer ; Poor, H. Vincent
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
fDate :
1/1/1994 12:00:00 AM
Abstract :
Decentralized detection problems are studied where the sensor distributions are not specified completely. The sensor distributions are assumed to belong to known uncertainty classes. It is shown for a broad class of such problems that a set of least favorable distributions exists for minimax robust testing between the hypotheses. It is hence established that the corresponding minimax robust tests are solutions to simple decentralized detection problems for which the sensor distributions are specified to be the least favorable distributions
Keywords :
estimation theory; minimax techniques; probability; sensor fusion; signal detection; hypotheses; minimax robust decentralized detection; minimax robust testing; probability distributions; sensor distributions; sequential detection; uncertainty classes; Bayesian methods; Capacitive sensors; Closed-form solution; Helium; Minimax techniques; Probability distribution; Robustness; Sensor fusion; Testing; Uncertainty;
Journal_Title :
Information Theory, IEEE Transactions on
