1 resultado para Feasibility analysis.
em University of Queensland eSpace - Australia
Filtro por publicador
- Repository Napier (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (9)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (3)
- Aquatic Commons (12)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (2)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (4)
- Aston University Research Archive (17)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (4)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (4)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (27)
- Bucknell University Digital Commons - Pensilvania - USA (2)
- Cambridge University Engineering Department Publications Database (1)
- CentAUR: Central Archive University of Reading - UK (7)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (17)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- Dalarna University College Electronic Archive (1)
- Deakin Research Online - Australia (23)
- Digital Commons - Michigan Tech (2)
- Digital Commons @ DU | University of Denver Research (1)
- Digital Commons at Florida International University (5)
- DigitalCommons@The Texas Medical Center (9)
- DigitalCommons@University of Nebraska - Lincoln (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (1)
- DRUM (Digital Repository at the University of Maryland) (3)
- Duke University (2)
- FUNDAJ - Fundação Joaquim Nabuco (1)
- Glasgow Theses Service (1)
- Greenwich Academic Literature Archive - UK (1)
- Helda - Digital Repository of University of Helsinki (5)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (1)
- Indian Institute of Science - Bangalore - Índia (10)
- Instituto Politécnico do Porto, Portugal (5)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (1)
- Laboratório Nacional de Energia e Geologia - Portugal (1)
- Memorial University Research Repository (1)
- National Center for Biotechnology Information - NCBI (3)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (1)
- Publishing Network for Geoscientific & Environmental Data (2)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (19)
- Queensland University of Technology - ePrints Archive (608)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositorio Académico de la Universidad Nacional de Costa Rica (1)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (1)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositorio Institucional da UFLA (RIUFLA) (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (32)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (1)
- Scientific Open-access Literature Archive and Repository (1)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (15)
- Universidade dos Açores - Portugal (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (14)
- Université de Montréal, Canada (2)
- University of Michigan (42)
- University of Queensland eSpace - Australia (1)
- University of Washington (2)
- WestminsterResearch - UK (1)
Resumo:
This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.