Separation and Estimation of Periodic/Aperiodic State
Hisayoshi Muramatsu

TL;DR
This paper introduces a novel separation filter based on state definitions to distinguish and estimate quasi-periodic and quasi-aperiodic states within complex systems, enhancing control strategies.
Contribution
It defines new state categories and develops a separation filter combined with a Kalman filter for improved state estimation.
Findings
Proves linearity of periodic-pass and aperiodic-pass functions.
Establishes orthogonality of quasi-periodic and quasi-aperiodic states.
Designs an integrated filter for state separation and estimation.
Abstract
Periodicity and aperiodicity can exist in a state simultaneously and typically become quasi-periodicity and quasi-aperiodicity in a dynamically changing state. The quasi-periodic and quasi-aperiodic states existing in the periodic/aperiodic state mostly correspond to different phenomena and require different controls. For separation control of these states, this paper defines the periodic/aperiodic, quasi-periodic, and quasi-aperiodic states to construct a periodic/aperiodic separation filter that separates the periodic/aperiodic state into the quasi-periodic and quasi-aperiodic states. Based on these definitions, the linearity of periodic-pass and aperiodic-pass functions and the orthogonality of quasi-periodic and quasi-aperiodic state functions are proved. Subsequently, the periodic/aperiodic separation filter composed of periodic-pass and aperiodic-pass filters that realize the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsChaos control and synchronization · Neural Networks Stability and Synchronization · Advanced Memory and Neural Computing
