Abstract Due to the complex space environment, spacecraft telemetry signals are accompanied by a large amount of noise, and accuracy fault diagnosis is low directly using original signals. This paper proposes method for control systems based on principal component analysis (PCA) residual network (ResNet). Firstly, grayscale images generated denoising signal system through PCA; Secondly, input i...

Principal Components Analysis (PCA), which is more recently referred to as Proper Orthogonal Decomposition (POD) in the literature, is a popular technique in many fields of engineering, science, and mathematics. The benefit of PCA for dynamical systems comes from its ability to detect and rank the dominant coherent spatial structures of dynamic response, such as operating deflection shapes or m...

BACKGROUND The present study aimed to compare the expression of liver kinase B1 (LKB1) in prostate cancer (PCa) tissues and the paired adjacent tissues, then to evaluate the statistical relationship between LKB1 expression and prognosis of PCa patients. MATERIAL AND METHODS The relative expression of LKB1 at mRNA level was detected by quantitative real-time polymerase chain reaction (qRT-PCR). ...

We analyzed a statistical model of diaphragm motion using regular principal component analysis (PCA) and generalized N-dimensional PCA (GND-PCA). First, we generate 4D MRI of respiratory motion from 2D MRI using an intersection profile method. We then extract semiautomatically the diaphragm boundary from the 4D-MRI to get subject-specific diaphragm motion. In order to build a general statistica...