Cognitive Inference and Signal Processing in Adversarial Uncertain Environments

为了收集、处理数据并使其可供广泛的潜在应用程序随时访问，各种网络技术正在高度分布式的体系结构中涌现，以适应数量和类型不断增加的不同类型的传感器。提出的研究计划(RP)的目标是发明和分析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和敌对的环境(URP将以高级和低成本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。最近多个行业在智能、机器学习和信号处理领域创造了大量就业机会，证明了这项研究的及时性。经过培训以填补这些必要角色的HQP对于支持在加拿大企业的有利可图投资至关重要。

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.