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Abstract
  • We present a novel learning scheme to imprint stable vector
    fields into Extreme Learning Machines (ELMs). The networks represent
    movements, where asymptotic stability is incorporated through constraints
    derived from Lyapunov stability theory. We show that our approach successfully
    performs stable and smooth point-to-point movements learned
    from human handwriting movements.
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