Detecting dynamical states from noisy time series using bicoherence

Research article (Nonlinear Dynamics, 2017) · cited 11× · AI/ML
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Detecting dynamical states from noisy time series using bicoherence

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Detecting dynamical states from noisy time series using bicoherence is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Detecting dynamical states from noisy time series using bicoherence. Retrieved May 24, 2026, from https://4ort.xyz/entity/detecting-dynamical-states-from-noisy-time-series-using-bicoherence
MLA “Detecting dynamical states from noisy time series using bicoherence.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/detecting-dynamical-states-from-noisy-time-series-using-bicoherence.
BibTeX @misc{4ortxyz_detecting-dynamical-states-from-noisy-time-series-using-bicoherence_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Detecting dynamical states from noisy time series using bicoherence}}, year = {2026}, url = {https://4ort.xyz/entity/detecting-dynamical-states-from-noisy-time-series-using-bicoherence}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Detecting dynamical states from noisy time series using bicoherence — https://4ort.xyz/entity/detecting-dynamical-states-from-noisy-time-series-using-bicoherence (retrieved 2026-05-24)

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