Title :
Data representation in HOSVD-DCT based domain
Author :
Rovid, Andras ; Szeidl, Laszlo ; Varlaki, Peter
Author_Institution :
John von Neumann Fac. of Infomatics, Obuda Univ., Budapest, Hungary
Abstract :
The paper describes an approach for data representation and processing in the so called HOSVD-DCT based domain which combines the higher order singular value decomposition (HOSVD) with the discrete cosine transformation (DCT). The key idea is to express the multivariate function by an orthonormal set of one variable specific functions and perform DCT on those components which are less significant from the application point of view in order to ensure finer grained processing. It is advantageous also in case of system identification, where the behaviour of the system can be approximated by blending locally identified models. In this case the proposed method can efficiently be applied.
Keywords :
data structures; discrete cosine transforms; image representation; singular value decomposition; HOSVD-DCT based domain; data processing; data representation; digital image representation; discrete cosine transformation; higher order singular value decomposition; multivariate function; orthonormal set; system identification; variable specific functions; Approximation methods; Discrete cosine transforms; Feature extraction; Loading; Matrix decomposition; Singular value decomposition; Tensile stress;
Conference_Titel :
Intelligent Engineering Systems (INES), 2013 IEEE 17th International Conference on
Conference_Location :
San Jose
Print_ISBN :
978-1-4799-0828-8
DOI :
10.1109/INES.2013.6632791