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Abstract

According to one embodiment, a waveform signal processing system according to an embodiment includes a neural network, a learner, and an extractor. The neural network is configured to generate at least first time-series data on noise and second time-series data on a signal other than noise on the basis of input random noise. The learner is configured to update parameters of the neural network on the basis of a loss function including a main limitation term of which a value becomes lower as synthetic time-series data obtained by adding the first time-series data and the second time-series data generated by the neural network and an observed time-series waveform including noise become more similar to each other. The extractor is configured to extract at least one of the first time-series data and the second time-series data generated by the neural network as a target signal on the basis of the parameters updated by the learner.

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