Quantum computing for accelerating cross-correlations intensive applications in signal processing

Despite their importance as subfields of mathematics and engineering, signal and image processing have not received much attention in the field of quantum computation. Cross-correlations are instrumental to all the aforementioned fields. In this article we help fill this void by providing two quantum algorithms, one for computing and storing cross-correlations, and one for implementing the expectation maximization maximum likelihood algorithm. In addition we show that the quantum expectation maximization maximum likelihood algorithm has a quadratic speed-up compared to the classical analog.

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