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Further, the <inline-formula><tex-math id=\"M1\">\\begin{document}$ \\ell_{2,1} $\\end{document}<\/tex-math><\/inline-formula>-norm is employed to reduce redundancy and avoid overfitting, which facilitates its interpretability. In order to solve the proposed SCR, an efficient alternating optimization algorithm is developed with convergence analysis. Finally, some experimental studies on a simulated example and the benchmark Tennessee Eastman process are conducted to demonstrate the superiority over the classical CCA in terms of the false alarm rate and fault detection rate. The detection results indicate that the proposed method is promising.<\/p><\/jats:p>","DOI":"10.3934\/mfc.2021010","type":"journal-article","created":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T01:09:11Z","timestamp":1627607351000},"page":"167","source":"Crossref","is-referenced-by-count":1,"title":["A novel scheme for multivariate statistical fault detection with application to the Tennessee Eastman process"],"prefix":"10.3934","volume":"4","author":[{"given":"Nana","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingjing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianchao","family":"Xiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2321","reference":[{"key":"key-10.3934\/mfc.2021010-1","doi-asserted-by":"publisher","unstructured":"H. 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