Sensor-Adaptive Signal Processing for Dynamic Decision Making

用于动态决策的传感器自适应信号处理

• 批准号: 251246-2013
• 负责人: Krishnamurthy, Vikram
• 金额: $ 5.46万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=547663
• 关键词: Sensor; Adaptive; Signal; Processing; Dynamic

This project conducts fundamental research in adaptive decision making in signal processing systems. It involves the interplay of Bayesian signal processing, stochastic optimization, stochastic control and game theory. Such adaptive decision making problems have recently received significant attention in diverse areas including sensor networks, cognitive radars, biosensing, and automated decision systems. These problems transcend classical statistical signal processing (which deals with extracting signals from noisy measure- ments) to address the deeper issue of how sensors and signal processing algorithms can use feedback control to adapt to their environment thereby leading to a smart reconfigurable sensing systems.

本项目对信号处理系统中的自适应决策进行基础性研究。它涉及贝叶斯信号处理、随机优化、随机控制和博弈论的相互作用。这种自适应决策问题最近在传感器网络、认知雷达、生物传感和自动决策系统等不同领域受到了极大的关注。这些问题超越了传统的统计信号处理(从噪声测量中提取信号)，解决了传感器和信号处理算法如何使用反馈控制来适应环境的更深层次问题，从而导致了智能可重构传感系统。