论文标题
使用量度和渐近马尔可夫链的更改进行了强烈的对话
Strong Converses using Change of Measure and Asymptotic Markov Chains
论文作者
论文摘要
本文的主要贡献是$ k $ -HOP分布式假设测试针对独立性的强烈相反结果，在马尔可夫条件下有多个（中级）决策中心。我们的结果表明，在所有终端中可以同时实现的类型II误差指数集并不取决于最大允许的类型I误差概率。我们强有力的相反证明是基于量度论证的改变以及特定马尔可夫链的渐近证明。此证明方法也可以用于其他相反的证明，并且很有吸引力，因为它不需要像以前的相关证明那样求助于变分的特征或爆炸方法。
The main contribution of this paper is a strong converse result for $K$-hop distributed hypothesis testing against independence with multiple (intermediate) decision centers under a Markov condition. Our result shows that the set of type-II error exponents that can simultaneously be achieved at all the terminals does not depend on the maximum permissible type-I error probabilities. Our strong converse proof is based on a change of measure argument and on the asymptotic proof of specific Markov chains. This proof method can also be used for other converse proofs, and is appealing because it does not require resorting to variational characterizations or blowing-up methods as in previous related proofs.
