Cognitive Inference and Signal Processing in Adversarial Uncertain Environments

为了收集数据，处理并使其可用于广泛的潜在应用并易于访问，各种网络技术正在高度分布式架构中出现，用于增加异构传感器的数量和类型。建议的研究计划（RP）的目标是发明和分析认知分布式算法处理数据。传统的方法在实践中往往失败，因为它们的设计没有考虑到不确定和敌对的环境（UThis 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，使关键系统能够学习和认知地在U中运行。机器学习和信号处理。经过培训的HQP能够胜任这些必要的角色，这对于支持加拿大企业的盈利性投资至关重要。

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.