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- W2370542412 abstract "An on-line learning algorithm for least squares support vector machine(LS-SVM) is proposed to resolve the problem of matrix dimension expending in the on-line approximation of nonlinear function.Based on the theory of sliding window,a data region which is sliding with time is built.The data region keeps the length invariant and data updating by means of receiving the new data and omitting the old data,and the on-line learning of the model is realized in this way.The simulation result shows the feasibility of the algorithm proposed." @default.
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- W2370542412 date "2011-01-01" @default.
- W2370542412 modified "2023-09-26" @default.
- W2370542412 title "Study on the On-line Learning Algorithm for Least Squares Support Vector Machine" @default.
- W2370542412 hasPublicationYear "2011" @default.
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