In this paper, we predict the propagation characteristics of indoor radio waves at 2450 MHz frequency set up in an office building. Based on a time domain finite difference algorithm, a numerical model of a single floor of the simulated office building gives the relationship between the office environment and the propagation characteristics, and the calculated received signal strength indication (RSSI) distribution and path loss at 2450 MHz frequency are discussed. It is clarified that the path loss increases due to the presence of internal obstructions. In addition, the RSSI distribution in the observation plane indicates that the higher the complexity of the indoor spatial environment, the weaker the transmitted power of the signal.
Medical image segmentation plays an increasingly important role in the whole field of image processing. Among them, the method of tumor segmentation has been paid more attention because of its special clinical significance. To solve the problems of traditional pulse-coupled neural network (PCNN) in the field of medical image processing, an internalactivity-changed FCMSPCNN (IAC-FCMSPCNN) is proposed to segment pulmonary nodules. This method further optimizes and improves the synaptic weight matrix, link strength and dynamic threshold, and reduces the number of model iterations. Experimental verification on five images in PET-CT lung cancer image library shows that the proposed method has good segmentation effect and is more suitable for clinical medical image segmentation.
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