Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices

Mohammad Mohammadi; Michael Biehl; Andrea Villmann; Thomas Villmann

doi:10.1007/978-3-319-59063-9_12

Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices

Mohammad Mohammadi
, Michael Biehl
, Andrea Villmann
, Thomas Villmann

Intelligente Systemen

Onderzoeksoutput: Conference contribution › Academic › peer review

4 Citaten (Scopus)

Originele taal-2	English
Titel	International Conference on Artificial Intelligence and Soft Computing
Subtitel	ICAISC 2017
Redacteuren	L. Rutkowski
Plaats van productie	Cham
Uitgeverij	Springer
Pagina's	131-142
Aantal pagina's	12
ISBN van elektronische versie	978-3-319-59063-9
ISBN van geprinte versie	978-3-319-59062-2
DOI's	https://doi.org/10.1007/978-3-319-59063-9_12
Status	Published - 2017

Publicatie series

Naam	Lecture Notes in Computer Science
Uitgeverij	Springer
Volume	10245

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10.1007/978-3-319-59063-9_12

https://link.springer.com/chapter/10.1007/978-3-319-59063-9_12

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Mohammadi, M., Biehl, M., Villmann, A., & Villmann, T. (2017). Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. In L. Rutkowski (editor), International Conference on Artificial Intelligence and Soft Computing: ICAISC 2017 (blz. 131-142). (Lecture Notes in Computer Science; Vol. 10245). Springer. https://doi.org/10.1007/978-3-319-59063-9_12

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title = "Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices",

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language = "English",

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Mohammadi, M, Biehl, M, Villmann, A & Villmann, T 2017, Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. in L Rutkowski (reds.), International Conference on Artificial Intelligence and Soft Computing: ICAISC 2017. Lecture Notes in Computer Science, vol. 10245, Springer, Cham, blz. 131-142. https://doi.org/10.1007/978-3-319-59063-9_12

Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. / Mohammadi, Mohammad; Biehl, Michael; Villmann, Andrea et al.
International Conference on Artificial Intelligence and Soft Computing: ICAISC 2017. reds. / L. Rutkowski. Cham: Springer, 2017. blz. 131-142 (Lecture Notes in Computer Science; Vol. 10245).

Onderzoeksoutput: Conference contribution › Academic › peer review

TY - GEN

T1 - Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices

AU - Mohammadi, Mohammad

AU - Biehl, Michael

AU - Villmann, Andrea

AU - Villmann, Thomas

PY - 2017

Y1 - 2017

U2 - 10.1007/978-3-319-59063-9_12

DO - 10.1007/978-3-319-59063-9_12

M3 - Conference contribution

SN - 978-3-319-59062-2

T3 - Lecture Notes in Computer Science

SP - 131

EP - 142

BT - International Conference on Artificial Intelligence and Soft Computing

A2 - Rutkowski, L.

PB - Springer

CY - Cham

ER -

Mohammadi M, Biehl M, Villmann A, Villmann T. Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. In Rutkowski L, redacteur, International Conference on Artificial Intelligence and Soft Computing: ICAISC 2017. Cham: Springer. 2017. blz. 131-142. (Lecture Notes in Computer Science). Epub 2017 mei 27. doi: 10.1007/978-3-319-59063-9_12