Nuclear magnetic resonance (NMR) serves as an indispensable tool in revealing physical, chemical and structural information about molecules. We present a hypercomplex low rank approach to reconstruct hypercomplex NMR spectrum reconstruction. We first introduce an adjoint matrix operation to convert the hypercomplex signal into complex matrix and then propose a low-rank model and algorithm to reconstruct hypercomplex signal. The experiment results demonstrate that the proposed method provides a fast and high-fidelity reconstruction of hypercomplex NMR data. Furthermore, we made the method available at an open-access and easy-to-use cloud computing platform.
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