Several Krylov-type procedures are introduced that generalize matrix Krylov methods for tensor computations. They are denoted minimal Krylov recursion, maximal Krylov recursion, and contracted tensor product Krylov recursion. It is proved that, for a given tensor A with multilinear rank-(p, q, r), the minimal Krylov recursion extracts the correct subspaces associated to the tensor in p+ q+r num...

Electroencephalography (EEG) is one fundamental tool for functional brain imaging. EEG signals tend to be represented by a vector or a matrix to facilitate data processing and analysis with generally understood methodologies like time-series analysis, spectral analysis and matrix decomposition. Indeed, EEG signals are often naturally born with more than two modes of time and space, and they can...

Conditional probability tables (CPTs) of threshold functions represent a generalization of two popular models – noisy-or and noisy-and. They constitute an alternative to these two models in case they are too rough. When using the standard inference techniques the inference complexity is exponential with respect to the number of parents of a variable. In case the CPTs take a special form (in thi...

The popular tensor train (TT) and ring (TR) decompositions have achieved promising results in science engineering. However, TT TR only establish an operation between adjacent two factors are highly sensitive to the permutation of modes, leading inadequate inflexible representation. In this paper, we propose a generalized decomposition, which decomposes Nth-order into set establishes any factors...

We establish several mathematical and computational properties of the nuclear norm for higher-order tensors. We show that like tensor rank, tensor nuclear norm is dependent on the choice of base field — the value of the nuclear norm of a real 3-tensor depends on whether we regard it as a real 3-tensor or a complex 3-tensor with real entries. We show that every tensor has a nuclear norm attainin...

Using the tensor product variety introduced in [6] and [9], the complete structure of the tensor product of a finite number of integrable highest weight modules of Uq(sl 2) is recovered. In particular, the elementary basis, Lusztig's canonical basis, and the basis adapted to the decomposition of the tensor product into simple modules are all exhibited as distinguished elements of certain spaces...

Using the tensor product variety introduced in [6] and [7], the complete structure of the tensor product of a finite number of integrable highest weight modules of Uq(sl 2) is recovered. In particular, the elementary basis, Lusztig's canonical basis, and the basis adapted to the decomposition of the tensor product into simple modules are all exhibited as distinguished elements of certain spaces...

Using the tensor product variety introduced in [6] and [7], the complete structure of the tensor product of a finite number of integrable highest weight modules of Uq(sl 2) is recovered. In particular, the elementary basis, Lusztig's canonical basis, and the basis adapted to the decomposition of the tensor product into simple modules are all exhibited as distinguished elements of certain spaces...

While elastoplasticity theories at small deformations are well established for various materials, elastoplasticity theories at large deformations are still a subject of controversy and lively discussions. Among the approaches to finite elastoplasticity two became especially popular. The first, implemented in the commercial finite element codes, is based on the introduction of a hypoelastic cons...