publication . Article . Other literature type . 2006

MATLAB tensor classes for fast algorithm prototyping

Tamara Kolda;
Restricted
  • Published: 01 Dec 2006 Journal: ACM Transactions on Mathematical Software, volume 32, pages 635-653 (issn: 0098-3500, eissn: 1557-7295, Copyright policy)
  • Publisher: Association for Computing Machinery (ACM)
Abstract
Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to psychometrics. We describe four MATLAB classes for tensor manipulations that can be used for fast algorithm prototyping. The tensor class extends the functionality of MATLAB's multidimensional arrays by supporting additional operations such as tensor multiplication. The tensorlaslmatrix class supports the “matricization” of a tensor, that is, the conversion of a tensor to a matrix (and vice versa), a commonly used operation in many algorithms. Two additional classes represent tensors stored in decomposed formats: cpltensor and tucker...
Subjects
ACM Computing Classification System: MathematicsofComputing_NUMERICALANALYSISComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue