LP-Conjugation: Unraveling Time Series Dynamics through Chaotic Map Convolution

LP-Conjugation, introduced by Padua and Libao, is a versatile method used in solving the Inverse Frobenius-Perron problem (IFPP) for chaotic systems based on time series data. While their initial work focused logistic map prime gap data, this article highlights broader significance of LP-Conjugation as powerful tool IFPP. Any can be employed with established data to reconstruct unknown maps. utilizes known ?(?) invariant distribution F(?) construct an H(?). The presents detailed proof, illustrating method's robustness adaptability. Further illustrations how from logistic-based sample also provided. Real-world examples demonstrate LP-Conjugation's efficacy diverse applications, solidifying its role valuable approach IFPP understanding dynamics.