Recovering Latent Signals From a Mixture of Measurements Using a Gaussian Process Prior.

IEEE Signal Processing Letters(2017)

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摘要
In sensing applications, sensors cannot always measure the latent quantity of interest at the required resolution, sometimes they can only acquire a blurred version of it due the sensor's transfer function. To recover latent signals when only noisy mixed measurements of the signal are available, we propose the Gaussian process mixture of measurements (GPMM), which models the latent signal as a Gau...
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关键词
Noise measurement,Weight measurement,Extraterrestrial measurements,Robot sensing systems,Linear systems,Gaussian processes
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