Zobrazeno 1 - 9 of 9 pro vyhledávání: '"Neural networks principal component analysis"'
1
Akademický článek
Comparison of Statistical Underlying Systematic Risk Factors and Betas Driving Returns on Equities
Autor: Rogelio Ladrón de Guevara Cortés, Salvador Torra Porras, Enric Monte Moreno
Publikováno v: Revista Mexicana de Economía y Finanzas Nueva Época REMEF, Vol 16, Iss 0, Pp e697-e697 (2021)
The objective of this paper is to compare four dimension reduction techniques used for extracting the underlying systematic risk factors driving returns on equities of the Mexican Market. The methodology used compares the results of estimation produc
Externí odkaz: https://doaj.org/article/c3a6109b012848079af0118621b487fe
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2
Akademický článek
Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange
Autor: Rogelio, Salvador Torra Porras, Enric Monte Moreno
Publikováno v: Revista Finanzas y Política Económica, Vol 13, Iss 2 (2021)
This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extra
Externí odkaz: https://doaj.org/article/f5ca7992a66f4a33870e9400e1b74225
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3
Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange
Autor: Salvador Torra Porras, Rogelio, Enric Monte Moreno
Publikováno v: Revista Finanzas y Política Económica, Volume: 13, Issue: 2, Pages: 513-543, Published: 12 APR 2022
This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis, and Neural Networks Principal Component Analysis, which are used as techniques for extr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9418d5c8becde871113508e54c742ee
https://doi.org/10.14718/revfinanzpolitecon.v13.n2.2021.9
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4
Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange
Autor: Enrique Monte, Rogelio Ladron de Guevara Cortes, Salvador Torra
Publikováno v: Revista Finanzas y Política Económica, Vol 13, Iss 2 (2021)
This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extra
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f6b8334ca9965ff88924f24a5dda8c5
https://doi.org/10.14718/revfinanzpolitecon.3740
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5
Statistical and computational techniques for extraction of underlying systematic risk factors: A comparative study in the Mexican stock exchange
Autor: Ladrón de Guevara Cortés, Rogelio, Torra Porras, Salvador, Monte Moreno, Enrique|||0000-0002-4907-0494
Publikováno v: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis, and Neural Networks Principal Component Analysis, which are used as techniques for extr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a310b98fa9590f33932a1bfd51991999
https://hdl.handle.net/10983/29450
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6
Akademický článek
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7
Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson’s Disease in 3D Nuclear Imaging Data
Autor: Klaus L. Leenders, Maria Rodriguez Oroz, Sanne K. Meles, Natasha M. Maurits, Octavio E. Martinez Manzanera, Flavio Nobili, Silvia Morbelli, Dario Arnaldi, Remco J. Renken, Jose A. Obeso, Marco Pagani
Publikováno v: International Journal of Neural Systems, 29(9):1950010
Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). Fluorodeo
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecc2093a0713cac298d4b974dec46cf6
https://doi.org/10.1142/s0129065719500102
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8
Akademický článek
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9
Temporal responses of chemically diverse sensor arrays for machine olfaction using artificial intelligence
Autor: Ryman, Shaun K.
The human olfactory system can classify new odors in a dynamic environment with varying odor complexity and concentration, while simultaneously reducing the influence of stable background odors. Replication of this capability has remained an active a
Externí odkaz: http://hdl.handle.net/1993/31056
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