Data training method for applying deep learning to compressed sensing reconstruction
A technology of compressed sensing and data training, which is applied in the field of data training where deep learning is applied to compressed sensing reconstruction, which can solve the problems that cannot be directly applied to compressed sensing reconstruction, and achieve the effect of improving the accuracy of signal reconstruction
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[0020] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the examples. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.
[0021] A data training method for applying deep learning to compressed sensing reconstruction provided by an embodiment of the present invention includes the following steps:
[0022] Step 1. Signal sparsification. Select a real data (a voice or an image) as the signal x∈R N , according to the characteristics of the signal, select the sparse basis Ψ∈R N×N , calculate the coefficient s=Ψ of the signal x under the sparse basis Ψ -1 x. Among them, the sparse base can choose an orthogonal wavelet transform base, a discrete cosine transform base or other transform bases, and the num...
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