Application of Non-negative Matrix Factorization to Signal Curve Recognition in A Real-time Control Software
Qian Bin, Huang Dexian, Wang Xiong · 2006
This paper aims at upgrading the current pattern of electronic tubes real-time control software (ETRCS) application. It presents a new method based on non-negative matrix factorization (NMF) to recognize several types of curves in ETRCS. Theoretically, NMF method can extract the part features of objects that resemble intuitive notions in an unsupervised way, which is similar to human visual perception. The test results based on real data indicate that this method can effectively recognize different curves, and will contribute to improving the tube's quality.