Tensor network subspace identification of polynomial state space models

Tensor network subspace identification of polynomial state space models

This article introduces a tensor network subspace algorithm for the identification of specific polynomial state space models. The polynomial nonlinearity in the state space model is completely written in terms of a tensor network, thus avoiding the curse of dimensionality. We also prove how the block Hankel data matrices in the subspace method can be exactly represented by low rank tensor netwo...

Identification of Approximative Nonlinear State-space Models by Subspace Methods

A subspace identification algorithm for state-affine state-space systems which allows to approximate nonlinear systems arbitrarily well is derived. The proposed algorithm depends on an approximation step where a detailed approximation error analysis is provided. A special case is presented in which this approximation error vanishes. To tackle higher-order systems and ill-posed problems a regula...

Identification of nonlinear systems using Polynomial Nonlinear State Space models

Tensor Space Models for Authorship Identification

Authorship identification can be viewed as a text categorization task. However, in this task the most frequent features appear to be the most important discriminators, there is usually a shortage of training texts, and the training texts are rarely evenly distributed over the authors. To cope with these problems, we propose tensors of second order for representing the stylistic properties of te...

Recursive subspace identification of linear and non-linear Wiener state-space models

The problem of MIMO recursive identiication is considered and analyzed within the framework of subspace-based state space system identiication (4SID). With respect to previous contributions to this area, in this paper the use of recent signal processing algorithms for the recursive update of the SVD is proposed. To accommodate for arbitrary correlation of the disturbances, an instrumental varia...