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Gunes, Bilal (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
The major bottleneck in state-of-the-art Linear Parameter Varying (LPV) subspace methods is the curse-of-dimensionality during the first regression step. In this paper, the origin of the curse-of-dimensionality is pinpointed and subsequently a novel method is proposed which does not suffer from this bottleneck. The problem is related to the...
journal article 2017
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Gunes, Bilal (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
In this paper, we present a novel multiple input multiple output (MIMO) linear parameter varying (LPV) state-space refinement system identification algorithm that uses tensor networks. Its novelty mainly lies in representing the LPV sub-Markov parameters, data and state-revealing matrix condensely and in exact manner using specific tensor...
journal article 2018