Event detection and classification from multimodal time series with application to neural data
Nitin Sadras,
Bijan Pesaran,
Maryam M Shanechi
Abstract:Objective: The detection of events in time-series data is a common signal-processing problem. When the data can be modeled as a known template signal with an unknown delay in Gaussian noise, detection of the template signal can be done with a traditional matched filter. However, in many applications, the event of interest is represented in multimodal data consisting of both Gaussian and point-process time series. Neuroscience experiments for example can simultaneously record multimodal neural signals such as l… Show more
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