Location awareness is crucial for numerous emerging wireless indoor applications. Deep learning algorithms have demonstrated the potential for achieving the required level of positioning accuracy in indoor environments. However, obtaining abundant labels for data-driven machine learning is costly in practical situations. As an effective solution to alleviating the insufficiency of labeled data for deep learning-based indoor positioning, deep semi-supervised learning (DSSL) can be employed to lessen the dependency on labeled data by exploiting potential patterns in unlabeled samples. In this paper, we propose an Adapted Mean Teacher (AMT) model within the DSSL paradigm for indoor fingerprint positioning by using a channel impulse response. To enhance the generalization of the trained model, we design an efficient implicit augmentation scheme for the training process in the AMT model. Furthermore, we develop a tailored residual network to efficiently extract location characteristics in the AMT framework. We conduct extensive simulation experiments for indoor scenarios with heavy non-line-of-sight conditions based on open datasets to demonstrate the effectiveness of our proposed AMT model. Numerical results indicate that the AMT model outperforms several consistency regularization methods and the pseudo-label method in terms of positioning accuracy and lower positioning latency, achieving a mean error of 90cm when using a small number of labels.

In order to improve the resolution and visual effect of the image, improve the contrast of the whole or part of the image and highlight the details of the image, this paper proposes an image enhancement method based on bi-cubic interpolation and singular value decomposition. Firstly, histogram equalization and bi-cubic interpolation are performed on the original image to better preserve the details of the image. Then, the processed image is decomposed into various resolution subbands by discrete wavelet transform. Then, the low-frequency subbands are decomposed by singular value decomposition, and the image is reconstructed by discrete wavelet reconstruction, The reconstructed image and the original image are matched by histogram. The experimental results show that the effect of this method is better.

DSB communication has been widely applied into the military communication. At the same time, the jamming technique to the DSB communication was studied in many countries. Through studied the modulation recognition and analyzed the envelope detecting technique, this paper present an new feature based on the envelope information. The efficient method to evaluate the DSB communication was proposed. The results of simulation test show its good performance.

To be aimed at the fact that Power system supply voltage is generally higher than the rated voltage of the load voltage. Using electromagnetic balance technology and PLC control technology, an automatic voltage regulator device have been designed to reduced voltage, and introduced the structure and the saving voltage principle of the automatic voltage regulator device. Through structural design and equipment selection, automatic voltage regulator device itself makes a very small loss, with significant energy-saving effect.