1 resultado para Interval Arithmetic Operations
em Massachusetts Institute of Technology
Filtro por publicador
- Adam Mickiewicz University Repository (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (1)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (3)
- Applied Math and Science Education Repository - Washington - USA (2)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archive of European Integration (59)
- Aston University Research Archive (3)
- Avian Conservation and Ecology - Eletronic Cientific Hournal - Écologie et conservation des oiseaux: (2)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (11)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (18)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (1)
- Biodiversity Heritage Library, United States (5)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (59)
- Brock University, Canada (7)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (6)
- CentAUR: Central Archive University of Reading - UK (53)
- Cochin University of Science & Technology (CUSAT), India (8)
- Collection Of Biostatistics Research Archive (8)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (31)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (27)
- CUNY Academic Works (4)
- Dalarna University College Electronic Archive (3)
- Department of Computer Science E-Repository - King's College London, Strand, London (2)
- Digital Commons - Michigan Tech (1)
- Digital Commons @ Winthrop University (2)
- Digital Peer Publishing (1)
- DigitalCommons@The Texas Medical Center (8)
- DigitalCommons@University of Nebraska - Lincoln (4)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (47)
- FUNDAJ - Fundação Joaquim Nabuco (1)
- Institute of Public Health in Ireland, Ireland (1)
- Instituto Politécnico de Leiria (1)
- Instituto Politécnico do Porto, Portugal (12)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (23)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Massachusetts Institute of Technology (1)
- Ministerio de Cultura, Spain (2)
- Portal do Conhecimento - Ministerio do Ensino Superior Ciencia e Inovacao, Cape Verde (1)
- Publishing Network for Geoscientific & Environmental Data (196)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (10)
- Repositório digital da Fundação Getúlio Vargas - FGV (6)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (68)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (5)
- School of Medicine, Washington University, United States (2)
- Scielo Saúde Pública - SP (27)
- Universidad Autónoma de Nuevo León, Mexico (6)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (2)
- Universidad Politécnica de Madrid (5)
- Universidade Complutense de Madrid (1)
- Universidade do Minho (2)
- Universidade dos Açores - Portugal (3)
- Universidade Federal do Pará (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (10)
- Universitat de Girona, Spain (11)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (4)
- Université de Lausanne, Switzerland (37)
- Université de Montréal, Canada (5)
- University of Connecticut - USA (1)
- University of Michigan (1)
- University of Queensland eSpace - Australia (29)
- University of Southampton, United Kingdom (1)
- University of Washington (1)
Resumo:
Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brain regions along the ventral pathway extract object features of increasing levels of complexity, accompanied by greater invariance in stimulus size, position, and orientation. Recent theoretical studies postulate a non-linear pooling function, such as the maximum (MAX) operation could be fundamental in achieving such invariance. In this paper, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Four canonical circuits are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we examine the relative performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each circuit and discuss their respective physiological considerations.