Minimum Bitrate Neuromorphic Encoding for Continuous-Time Gauss-Markov Processes

• 成果类型: Article
• 署名作者: Cuvelier, Travis; Ogden, Ronald; Tanaka, Takashi
• 署名单位: University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3419586
• 发表日期: 2025
• 页码: 50-64
• 关键词: sensors; Bit rate; Real-time systems; COSTS; Robot sensing systems; distortion; Rate-distortion; Continuous-time (CT) systems; Information theory; Kalman filters; networked control systems; optimal control

摘要

In this work, we study minimum data rate tracking of a dynamical system under a neuromorphic event-based sensing paradigm. We begin by bridging the gap between continuous-time (CT) system dynamics and information theory's causal rate distortion theory. We motivate the use of nonsingular source codes to quantify bitrates in event-based sampling schemes. This permits an analysis of minimum bitrate event-based tracking using tools already established in the control and information theory literature. We derive novel, nontrivial lower bounds to event-based sensing, and compare the lower bound with the performance of well-known schemes in the established literature.