In order to improve the diagnosis rate of wavelet neural network algorithm for the radar circuit, for the network during operation there is poor convergence, the training error and shortcomings easy to fall into local minimum, the network is unable to continue training and testing, proposing a new algorithm of increasing the momentum of the wavelet adaptive neural network, can make the network run more stable, faster learning rate; By the Matlab simulation experiments show that the diagnosis rate of the improved algorithm is much higher than the ordinary one.
Dental cone beam CT (CBCT) scans, due to their low radiation dose, are now widely used in the medical diagnosis of patients’ oral cavity. The reconstruction of a panoramic view of the dental arch from the scanned CBCT data facilitates the dentist’s observation of the patient’s oral condition. The most important technique for reconstructing the dental arch panorama is the extraction of the dental arch curve accurately. The existing method is to rely on the experience of the dentist to manually connect the dental arch curve, or use techniques related to threshold segmentation to extract dental arch curve. These methods rely on the experience of dentists on the one hand. On the other hand, when there are interferences such as implants, metal tubes, braces or missing teeth in the patient’s mouth, the threshold calculation will be wrong. Based on this, this article starts with the histogram of CBCT data, and proposes a highly robust and fully automatic dental arch curve extraction method. In the actual experiment, the dental arch curves of 40 different patients were extracted, and all the dental arch curves can be accurately and automatically extracted, thus verifying the effectiveness of the proposed algorithm.
Transfer function is a very important parameter to evaluate the system performance, and it is one of the key methods to process and analyze information. First, the feasibility of this method is analyzed by the theory simulation in this paper. Second, the median is selected to filter the noise in the spectral data by comparing median filtering and Db3 wavelet filtering results. And then, the transfer function method is used on the data processing that captured by a linear CCD spectrometer. The experimental results show that the spectral data processing method base on the transfer function given in this paper is reasonable. This method can further improve the accuracy and the resolution of the instrument, and can make it possible to get a wide application of the CCD spectrometer.
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