Planar inverted F-shaped antenna resonant frequency prediction method based on semi-supervised learning
A semi-supervised learning and resonant frequency technology, applied in neural learning methods, biological neural network models, design optimization/simulation, etc., can solve the problems of many labeled samples, multiple calls, and long time consumption, and achieve satisfactory prediction accuracy and improve Efficiency and time-saving effects
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[0034] The technical solution of the present invention will be further described in conjunction with the accompanying drawings and embodiments.
[0035]The present invention aims at the problem that when the traditional supervised learning modeling method is used to model the resonant frequency of the PIFA antenna, relatively many labeled samples are required and the calculation time is too long. On the basis of the existing semi-supervised collaborative training, a A collaborative training method based on GP model and SVM model is proposed, and the resonant frequency of PIFA antenna is modeled, which reduces the amount of labeled data required for modeling and improves the accuracy of the model.
[0036] The present invention is a method for predicting the resonant frequency of a planar inverted-F antenna based on GP and SVM cooperative training, comprising the following steps:
[0037] Step 1: Modeling of GP and SVM
[0038] 1) Acquisition of training samples
[0039] A ma...
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