A modification of the lernmatrix for real valued data processing

José Juan Carbajal-Hernández; Luis P. Sánchez-Fernández; Luis A. Sánchez-Pérez; Jesús Ariel Carrasco-Ochoa; José Francisco Martínez-Trinidad

doi:10.1007/978-3-642-33275-3_60

A modification of the lernmatrix for real valued data processing

José Juan Carbajal-Hernández, Luis P. Sánchez-Fernández, Luis A. Sánchez-Pérez, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad

Centro de Investigación en Computación (CIC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

An associative memory is a binary relationship between inputs and outputs, which is stored in an M matrix. In this paper, we propose a modification of the Steinbuch Lernmatrix model in order to process real-valued patterns, avoiding binarization processes and reducing computational burden. The proposed model is used in experiments with noisy environments, where the performance and efficiency of the memory is proven. A comparison between the proposed and the original model shows a good response and efficiency in the classification process of the new Lernmatrix.

Original language	English
Title of host publication	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
Pages	487-494
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-33275-3_60
State	Published - 2012
Event	17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012 - Buenos Aires, Argentina Duration: 3 Sep 2012 → 6 Sep 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7441 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Country/Territory	Argentina
City	Buenos Aires
Period	3/09/12 → 6/09/12

Keywords

Associative memories
artificial intelligence
classifier
neurocomputing
pattern processing

Access to Document

10.1007/978-3-642-33275-3_60

Cite this

Carbajal-Hernández, J. J., Sánchez-Fernández, L. P., Sánchez-Pérez, L. A., Carrasco-Ochoa, J. A., & Martínez-Trinidad, J. F. (2012). A modification of the lernmatrix for real valued data processing. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings (pp. 487-494). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7441 LNCS). https://doi.org/10.1007/978-3-642-33275-3_60

Carbajal-Hernández, José Juan ; Sánchez-Fernández, Luis P. ; Sánchez-Pérez, Luis A. et al. / A modification of the lernmatrix for real valued data processing. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. pp. 487-494 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "An associative memory is a binary relationship between inputs and outputs, which is stored in an M matrix. In this paper, we propose a modification of the Steinbuch Lernmatrix model in order to process real-valued patterns, avoiding binarization processes and reducing computational burden. The proposed model is used in experiments with noisy environments, where the performance and efficiency of the memory is proven. A comparison between the proposed and the original model shows a good response and efficiency in the classification process of the new Lernmatrix.",

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year = "2012",

doi = "10.1007/978-3-642-33275-3_60",

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Carbajal-Hernández, JJ , Sánchez-Fernández, LP, Sánchez-Pérez, LA, Carrasco-Ochoa, JA & Martínez-Trinidad, JF 2012, A modification of the lernmatrix for real valued data processing. in Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7441 LNCS, pp. 487-494, 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012, Buenos Aires, Argentina, 3/09/12. https://doi.org/10.1007/978-3-642-33275-3_60

A modification of the lernmatrix for real valued data processing. / Carbajal-Hernández, José Juan ; Sánchez-Fernández, Luis P.; Sánchez-Pérez, Luis A. et al.
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. p. 487-494 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7441 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Carbajal-Hernández, José Juan

AU - Sánchez-Fernández, Luis P.

AU - Sánchez-Pérez, Luis A.

AU - Carrasco-Ochoa, Jesús Ariel

AU - Martínez-Trinidad, José Francisco

PY - 2012

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N2 - An associative memory is a binary relationship between inputs and outputs, which is stored in an M matrix. In this paper, we propose a modification of the Steinbuch Lernmatrix model in order to process real-valued patterns, avoiding binarization processes and reducing computational burden. The proposed model is used in experiments with noisy environments, where the performance and efficiency of the memory is proven. A comparison between the proposed and the original model shows a good response and efficiency in the classification process of the new Lernmatrix.

AB - An associative memory is a binary relationship between inputs and outputs, which is stored in an M matrix. In this paper, we propose a modification of the Steinbuch Lernmatrix model in order to process real-valued patterns, avoiding binarization processes and reducing computational burden. The proposed model is used in experiments with noisy environments, where the performance and efficiency of the memory is proven. A comparison between the proposed and the original model shows a good response and efficiency in the classification process of the new Lernmatrix.

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KW - artificial intelligence

KW - classifier

KW - neurocomputing

KW - pattern processing

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings

T2 - 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012

Y2 - 3 September 2012 through 6 September 2012

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Carbajal-Hernández JJ , Sánchez-Fernández LP, Sánchez-Pérez LA, Carrasco-Ochoa JA, Martínez-Trinidad JF. A modification of the lernmatrix for real valued data processing. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. p. 487-494. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-33275-3_60

A modification of the lernmatrix for real valued data processing

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Keywords

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