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Ideas to efficiently process signals

Research Achievements

Ideas to efficiently process signals

The analysis of non-stationary data is critical for the processing of sensing data because it can provide a localized time-frequency representation. Empirical Mode Decomposition can be used to estimate a signal's instantaneous frequency but suffers from poor performance in the presence of noise. IGERT participants have shown that the extraction of modes containing both signal and noise is the cause of poor instantaneous frequency estimation and have developed novel ideas to efficiently process signals from non-stationary data. This achievement has resulted in a publication in a peer-reviewed journal, a conference proceeding paper, and presentation in an international conference during this reporting period.