Decentralized Sequential Composite Hypothesis Test Based on One-Bit Communication

Decentralized Sequential Hypothesis Testing in Discrete Time

In this work we deal with the problem of decentralized sequential hypothesis testing in discrete time in the case that the sensors have full local memory. We adopt the scheme called Decentralized Sequential Probability Ratio Test (D-SPRT), which entails asynchronous communication of the sensors with the fusion center at random times. We prove that the D-SPRT is asymptotically optimal and we sho...

One-Sample Hypothesis Test Examples

Smart Fence: Decentralized Sequential Hypothesis Testing for Perimeter Security

This paper presents a practical solution for the fence-line intrusion detection problem. The MEMS based sensor platform is introduced along with its WirelessHART networking capabilities. A Decentralized Sequential Hypothesis Testing algorithm is studied at the theoretical level before being applied to the problem at hand. Results from several deployments show 100% detection rates within one sec...

AMultistage Procedure for Decentralized Sequential Multi-Hypothesis Testing Problems

We studied the problem of sequentially testing M ≥ 2 hypotheses with a decentralized sensor network system. In such a system, the local sensors observe raw data and then send quantized observations to a fusion center, which makes a final decision regarding hypothesis is true. Motivated by the two-stage tests in Wang and Mei (2011), we propose a multistage decentralized sequential test that prov...

Boosted multi-hypothesis sequential probability ratio test

In many computer vision classification and detection problems, the time to decision is no less important that the error rates. In the binary case, given the false positive and false negative rates, the optimal strategy minimizing the expected decision time is the Wald’s sequential probability ratio test (SPRT). Recently, Sochman and Matas proposed learning SPRT strategies from labeled examples ...