Published in Gowda, C.H., & Viswanathan, R. (1995). Robustness of decentralized tests with ε-contamination prior. IEEE Transactions on Information Theory, 41(4), 1164 - 1169. doi: 10.1109/18.391263 ©1995 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


We consider a decentralized detection problem where the prior density is not completely known, but is assumed to belong to an ε-contamination class. The expressions for the infimum and the supremum of the posterior probability that the parameter under question is in a given region, as the prior varies over the ε-contamination class, are derived. Numerical results are obtained for a specific case of an exponentially distributed observation and an exponentially distributed nominal prior. Asymptotic (as number of sensors tends to a large value) results are also obtained. The results illustrate the degree of robustness achieved with quantized observations as compared to unquantized observations.