{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:19:17Z","timestamp":1760242757871,"version":"build-2065373602"},"reference-count":13,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2016,6,24]],"date-time":"2016-06-24T00:00:00Z","timestamp":1466726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The minimum error entropy (MEE) algorithm is known to be superior in signal processing applications under impulsive noise. In this paper, based on the analysis of behavior of the optimum weight and the properties of robustness against impulsive noise, a normalized version of the MEE algorithm is proposed. The step size of the MEE algorithm is normalized with the power of input entropy that is estimated recursively for reducing its computational complexity. The proposed algorithm yields lower minimum MSE (mean squared error) and faster convergence speed simultaneously than the original MEE algorithm does in the equalization simulation. On the condition of the same convergence speed, its performance enhancement in steady state MSE is above 3 dB.<\/jats:p>","DOI":"10.3390\/e18070239","type":"journal-article","created":{"date-parts":[[2016,6,25]],"date-time":"2016-06-25T21:21:45Z","timestamp":1466889705000},"page":"239","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Normalized Minimum Error Entropy Algorithm with Recursive Power Estimation"],"prefix":"10.3390","volume":"18","author":[{"given":"Namyong","family":"Kim","sequence":"first","affiliation":[{"name":"Division of Electronic, Information and Communication Engineering, Kangwon National University, Samcheok 245-711, Korea"}]},{"given":"Kihyeon","family":"Kwon","sequence":"additional","affiliation":[{"name":"Division of Electronic, Information and Communication Engineering, Kangwon National University, Samcheok 245-711, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/JCN.2012.6184548","article-title":"Blind signal processing for impulsive noise channels","volume":"14","author":"Kim","year":"2012","journal-title":"J. Commu. Netw."},{"key":"ref_2","unstructured":"Armstrong, J., Shentu, J., Chai, C., and Suraweera, H. (2003, January 24\u201325). Analysis of impulse noise mitigation techniques for digital television systems. Proceedings of the 8th International OFDM-Workshop, 2003, Hamburg, Germany."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2187","DOI":"10.1109\/TSP.2006.872524","article-title":"Generalized correlation function: Definition, properties, and application to blind equalization","volume":"54","author":"Santamaria","year":"2006","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1780","DOI":"10.1109\/TSP.2002.1011217","article-title":"An entropy minimization algorithm for supervised training of nonlinear systems","volume":"50","author":"Erdogmus","year":"2002","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_5","first-page":"27","article-title":"Decision feedback equalizer algorithms based on error entropy criterion","volume":"12","author":"Kim","year":"2011","journal-title":"J. Internet Comput. Serv."},{"key":"ref_6","unstructured":"Kim, N. (2012, January 27\u201329). Performance analysis of entropy-based decision feedback algorithms in wireless shallow-water communications. Proceedings of KSII summer conference, Pyeongchang, Korea."},{"key":"ref_7","unstructured":"Kim, N., and Andonova, A. Computationally efficient methods for decision feedback algorithms based on minimum error entropy. 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Digital Communications, McGraw-Hill. [2nd ed.]."},{"key":"ref_13","first-page":"155","article-title":"A least squares approach to escalator algorithms for adaptive filtering","volume":"28","author":"Kim","year":"2006","journal-title":"J. Commu. Netw."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/18\/7\/239\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:24:46Z","timestamp":1760210686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/18\/7\/239"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,24]]},"references-count":13,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2016,7]]}},"alternative-id":["e18070239"],"URL":"https:\/\/doi.org\/10.3390\/e18070239","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2016,6,24]]}}}