Abstract
In the era of big data, software algorithms are improving rapidly, and machine learning algorithms are also widely used. In doing so, transmitting signals from quantum devices will also contribute to research on machine learning technology. Traditional machine learning networks face the problem of low efficiency and slow response when processing large amounts of complex data. Quantum computing technology offers supercomputing power to compensate for this shortcoming. Based on the advanced development of quantum machine learning and quantum computing technology, this paper combines machine learning technology. Integrate the regenerated kernel Hilbert space to complete the composition of the architecture, effectively improving the computational performance of machine learning.
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