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The aim of this paper is to propose a method that generates the minimum number of linear time-invariant systems (LTIs) used in an affine set to determine any parameter-dependent nonlinear system. The implication is to reduce the order of LTIs containing core tensor, as it can be quite large in the case of a big number of parameters, as previously every parameter was added to the parameter-space in...
The paper discusses how the Tensor Product structure is useful to simplify kinetic models of biological networks and provides basic mathematical tools one can start the kinetic model with. The applied method known as joint HOSVD-CPD decomposition is helpful to identify latent parameters, this work is utilizing it to determine the role of different parameters in a biochemical reaction. A case study...
Kronecker product (KP) approximation has recently been applied as a modeling and analysis tool on systems with hierarchical networked structure. In this paper, we propose a tensor product-based approach to the KP approximation problem with arbitrary number of factor matrices. The formulation involves a novel matrix-to-tensor transformation to convert the KP approximation problem to a best rank-(R1...
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