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This article discusses the challenge of extracting information from noisy environments in both classical and quantum computing. The authors propose a quantum smoothing filter for denoising electrocardiogram signals, which has a lower computational complexity compared to existing classical filters. The filter also takes advantage of the penta-diagonal Toeplitz structure, resulting in reduced gate costs. The authors provide performance metrics and show potential for better run-time complexity compared to classical techniques.
