Cognitive Inference and Signal Processing in Adversarial Uncertain Environments

为了收集数据、处理数据并使其易于获得广泛的潜在应用，各种网络技术正在以高度分布式的架构出现，以应对数量和类型不断增加的异构传感器。提出的研究计划（RP）的目标是发明和分析用于处理数据的认知分布式算法。传统方法在实践中经常失败，因为它们没有考虑到不确定性和对抗性环境（uu）。这个RP将以先进和低成本的认知信号处理算法的形式产生解决方案，并发明新的方法，使关键系统能够在uu中学习和认知操作。这项研究的时效性被智能、机器学习和信号处理领域的多个行业最近创造的大量就业机会所证明。HQP培训，以填补这些必要的角色是至关重要的，以支持在加拿大的商业有利可图的投资。

To collect data, process and make it available and readily accessible for a wide range of potential applications, various cyber technologies are emerging in a highly distributed architecture for increasing numbers and types of heterogeneous sensors. The goal of the proposed research program (RP) is to invent and analyze cognitive distributed algorithms for processing data. Traditional methods often fail in practice because they are not designed to take into account uncertain and adversarial environments (UThis RP will yield solutions in the form of advanced and low-cost cognitive signal processing algorithms and invent new methods to enable critical systems to learn and cognitively operate in UThe timeliness of this research is evidenced by recent massive job creation by multiple industries in the areas of intelligence, machine learning, and signal processing. HQP trained to fill these necessary roles are critical to supporting profitable investment in Canadian business.