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  • Image Reconstruction Based on Compressed Sensing Measurement Matrix Optimization Method
  • Abstract In this paper, the observation matrix and reconstruction algorithm of compressed sensing sampling theorem are studied. The advantages and disadvantages of greedy reconstruction algorithm are analyzed. The disadvantages of signal sparsely are preset in this algorithm. The sparsely adaptive estimation algorithm is proposed. The compressed sampling matching tracking algorithm supports the set selection and culling atomic standards to improve. The sparse step size adaptive compressed sampling matching tracking algorithm is proposed. The improved algorithm selects the sparsely as the step size to select the support set atom, and the maximum correlation value. Half of the threshold culling algorithm supports the…
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  • Based on Compressed Sensing of Orthogonal Matching Pursuit Algorithm Image Recovery
  • Abstract Compressive sensing theory mainly includes the sparsely of signal processing, the structure of the measurement matrix and reconstruction algorithm. Reconstruction algorithm is the core content of CS theory, that is, through the low dimensional sparse signal recovers the original signal accurately. This thesis based on the theory of CS to study further on seismic data reconstruction algorithm. We select orthogonal matching pursuit algorithm as a base reconstruction algorithm. Then do the specific research for the implementation principle, the structure of the algorithm of AOMP and make the signal simulation at the same time. In view of the OMP algorithm reconstruction…
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  • Research on Indoor Passive Positioning Technology Based on WiFi
  • Abstract In recent years, WiFi indoor positioning technology has become a hot research topic at home and abroad. However, at present, indoor positioning technology still has many problems in terms of practicability and stability, which seriously affects the accuracy of indoor positioning and increases the complexity of the calculation process. Aiming at the instability of RSS and the more complicated data processing, this paper proposes a low-frequency filtering method based on fast data convergence. Low-frequency filtering uses MATLAB for data fitting to filter out low-frequency data; data convergence combines the mean and multi-data parallel analysis process to achieve a good balance…
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  • An Expected Patch Log Likelihood Denoising Method Based on Internal and External Image Similarity
  • Abstract Nonlocal property is an important feature of natural images, which means that the patch matrix formed by similar image patches is low-rank. Meanwhile, learning good image priors is of great importance for image denoising. In this paper, we combine the image self-similarity with EPLL (Expected patch log likelihood) method, and propose an EPLL denoising model based on internal and external image similarity to improve the preservation of image details. The experiment results show that the validity of our method is proved from two aspects of visual and numerical results.
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  • Image Denoising Based on the Asymmetric Gaussian Mixture Model
  • Abstract In recent years, image restoration has become a huge subject, and finite hybrid model has been widely used in image denoising because of its easy modeling and strong explanatory results. The gaussian mixture model is the most common one. The existing image denoising methods usually assume that each component of the natural image is subject to the gaussian mixture model (GMM). However, this approach is not entirely reasonable. It is well known that most natural images are complex and their distribution is not entirely gaussian. As a result, there are still many problems that GMM cannot solve. This paper tries…
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  • Diagnostic Performance of Serum miR-586 and miR-493 in Patients with Osteosarcoma
  • Abstract This study aimed to explore the expression and diagnostic performance of miR-586 and miR-493 in patients with osteosarcoma. We enrolled 63 patients with osteosarcoma treated between May 2016 and May 2019 as the experimental group and 55 healthy volunteers who underwent physical examination during the same period as the control group. We detected miR-586 and miR-493 expression in serum, normal bone tissue, and tumor samples. We also evaluated the relationship between clinical indicators and the miR-586 and miR-493 expression levels. The correlation between the serum and osteosarcoma tissue expression of miR-586 and miR-493 was examined by Pearson analysis. Furthermore, the…
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  • Expression Changes, Prognostic Analysis and Risk Factors of miR-625-3p and miR-449a in Osteosarcoma Patients after Surgery
  • Abstract The expression changes of miR-625-3p and miR-449a in osteosarcoma patients after surgery is the critical study in this paper. Analysis of their prognosis and risk factors can be helpful in understanding the prognostic value for clinical purposes. Fifty-eight patients with osteosarcoma diagnosed in our hospital were considered as the research group (RG), and 52 health subjects at the same time were collected as the control group (CG). Fluorescence quantitative PCR (RTPCR) was employed to test the expression levels of miR-625-3p and miR-449a in the serum of subjects in both groups before surgery and patients in the RG after surgery. The…
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  • Sinomenium Inhibits the Viability of Hepatoma Carcinoma Cells through Activating IFNA2
  • Abstract Hepatocellular carcinoma (HCC) ranks the sixth place of most common cancers. Meanwhile, it is the tertiary mortality cause of cancer. There is no effective therapeutic method to prevent and treat the liver cancer. Sinomenine is a kind of Chinese traditional medicine herbal, it is reported that it can inhibit the viability of several cancer cells. The study is to explore whether sinomenine is also able to inhibit the cell viability of HCC and its potential mechanism. The IC50 of sinomenine in BEL-7402 cells was 5.351 mmol/L, and the IC50 of sinomenine in SMMC-7721 cells was 6.204 mmol/L. The gene expression…
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