{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:38:00Z","timestamp":1760243880767,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2010,1,26]],"date-time":"2010-01-26T00:00:00Z","timestamp":1264464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate.<\/jats:p>","DOI":"10.3390\/s100100952","type":"journal-article","created":{"date-parts":[[2010,1,26]],"date-time":"2010-01-26T09:15:31Z","timestamp":1264497331000},"page":"952-962","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II"],"prefix":"10.3390","volume":"10","author":[{"given":"Wilmar","family":"Hernandez","sequence":"first","affiliation":[{"name":"Department of Circuits and Systems, EUIT de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid (UPM), Campus Sur UPM, Ctra. Valencia km 7, Madrid 28031, Spain"}]},{"given":"Jes\u00fas","family":"De Vicente","sequence":"additional","affiliation":[{"name":"Department of Applied Physics, ETSI Industriales, Universidad Polit\u00e9cnica de Madrid, Calle Jos\u00e9 Gutierrez Abascal 2, Madrid 28006, Spain"}]},{"given":"Oleg Y.","family":"Sergiyenko","sequence":"additional","affiliation":[{"name":"Engineering Institute of Autonomous, University of Baja California, Mexicali, Baja California, M\u00e9xico"}]},{"given":"Eduardo","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[{"name":"EUIT de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid (UPM), Campus Sur UPM, Ctra. Valencia km 7, Madrid 28031, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2010,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"313","DOI":"10.3390\/s100100313","article-title":"Improving the response of accelerometers for automotive applications by using LMS adaptive filters","volume":"10","author":"Hernandez","year":"2010","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.3390\/s7010084","article-title":"A survey on optimal signal processing techniques applied to improve the performance of mechanical sensors in automotive applications","volume":"7","author":"Hernandez","year":"2007","journal-title":"Sensors"},{"key":"ref_3","unstructured":"Skogestad, S., and Posthlethwaite, I. (1996). Multivariable Feedback Control, John Wiley & Sons."},{"key":"ref_4","unstructured":"Zhou, K., Doyle, J.C., and Glover, K. (1996). 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