## Abstract

A decentralized sequential detection problem is considered where a set of sensors making independent observations must decide which of the given two hypotheses is true. Decision errors are penalized through a common cost function, and each time step taken by the sensors as a team is assigned a positive cost. It is shown that optimal sensor decision functions can be found in the class of generalized sequential probability ratio tests (GSPRTs) with monotonically convergent thresholds. A technique is presented for obtaining the optimal thresholds. The performance of the optimal policy is compared with that of a policy which uses SPRTs at each of the sensors.

Original language | English (US) |
---|---|

Pages (from-to) | 292-305 |

Number of pages | 14 |

Journal | Mathematics of Control, Signals, and Systems |

Volume | 7 |

Issue number | 4 |

DOIs | |

State | Published - Dec 1 1994 |

## Keywords

- Decentralized detection
- Distributed decision making
- Dynamic programming
- Optimal stopping rules
- Sequential analysis
- Stochastic teams

## ASJC Scopus subject areas

- Control and Systems Engineering
- Signal Processing
- Control and Optimization
- Applied Mathematics