Automatic recommendation method for signal reconstruction scheme
A technology for signal reconstruction and recommendation methods, applied in the direction of neural learning methods, neural architecture, digital data information retrieval, etc., can solve problems such as large computing costs and difficulty in obtaining recommended models, so as to reduce computing costs and solve the shortage of training samples , the effect of improving the accuracy
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[0053] In this example, if figure 1 As shown, an automatic recommendation method for a signal reconstruction scheme is performed as follows:
[0054] Step 1, using formula (1) to construct a single-objective optimization model for signal reconstruction;
[0055]
[0056] In formula (1), x represents the decision vector corresponding to the reconstructed signal, and x=(x 1 ,x 2 ,...,x i ,...,x d ), where x i Represents the i-th decision variable, and the i-th variable x i Corresponding to the i-th signal value, y is the observed signal, A is the perception matrix, f 1 (x) is the Lq paradigm of the reconstructed signal x, which is used to represent the sparse value of the reconstructed signal, q represents the parameter used to adjust the sparseness of the reconstructed signal, f 2 (x) represents the loss value of the reconstructed signal, and λ represents the weight, which is used to balance the sparsity and feasibility of the reconstructed signal;
[0057] Step 2. B...
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