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We propose two kinds of robust extreme learning machines (RELMs) based on the close-to-mean constraint and the small-residual constraint respectively to solve the problem of noisy measurements in indoor positioning systems (IPSs). We formulate both RELMs as second order cone programming problems. The fact that feature mapping in ELM is known to users is exploited to give the needed information for...
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