Plant Data Visualization Using Non-negative Matrix Factorization
نویسندگان
چکیده
Non-negative matrix factorization (NMF) is a method for dimensionality reduction and simplification of large data sets. Unlike tools such as principle components analysis (PCA) and factor analysis , NMF produces basis vectors that correspond to perceptible features in the original data. This is particularly useful when working with data where visual interpretation of the simplified representation is required. Typical data of this type is condition monitoring (CM) data, where visual interpretation of vibration spectra is a standard diagnostic tool. The res ults suggest that NMF processing of CM data simplifies the visual interpretation process, and opens the way for automation of this task. Copyright © 2005 IFAC
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تاریخ انتشار 2005