Extraction and Analysis of Multiple Periodic Motions in Video Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Signal Processing
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Time-frequency analysis has significant advances in two main directions: statistically optimized methods that extend the scope of time-frequency-based techniques from merely exploratory data analysis to more quantitative application and generalized joint signal representations that extend time-frequency-based methods to a richer class of nonstationary signals. This paper fuses the two advances by developing optimal detection and estimation techniques based on generalized joint signal representations. By generalizing the statistical methods developed for time-frequency representations to arbitrary joint signal representations, this paper develops a unified theory applicable to a wide variety of problems in nonstationary statistical signal processing