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This cost function is defined by the use of a likelihood score in a Gaussian Mixture Model (GMM) which is fitted to the observed attractor generated by the real system in state space. Using that learned GMM, a similarity score can be defined by the computed likelihood score of the model time series. The results show the adequacy of the proposed cost function.<\/jats:p>","DOI":"10.1142\/s0218127414500102","type":"journal-article","created":{"date-parts":[[2014,2,20]],"date-time":"2014-02-20T06:27:33Z","timestamp":1392877653000},"page":"1450010","source":"Crossref","is-referenced-by-count":82,"title":["Cost Function Based on Gaussian Mixture Model for Parameter Estimation of a Chaotic Circuit with a Hidden Attractor"],"prefix":"10.1142","volume":"24","author":[{"given":"Seng-Kin","family":"Lao","sequence":"first","affiliation":[{"name":"Department of Electromechanical Engineering, University of Macau, Avenida Padre Tom\u00e1s Pereira Taipa, Macau, P. R. 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