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Finally, the different performances of the algorithm of this paper and other kernel adaptive filtering algorithms as well as this paper\u2019s algorithm before and after quantization are compared in Mackey Glass chaotic time series as well as in system identification, confirming the superiority of the algorithm of this paper and the improved online vector quantization criterion. <\/jats:p>","DOI":"10.1142\/s0218001423590206","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T09:51:52Z","timestamp":1696845112000},"source":"Crossref","is-referenced-by-count":0,"title":["A Robust Kernel Least Mean Square Algorithm and its Quantization"],"prefix":"10.1142","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4161-5558","authenticated-orcid":false,"given":"Yuan-Lian","family":"Huo","sequence":"first","affiliation":[{"name":"College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730000, P. R. 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