Ivan Nunes da Silva; Danilo Hernane Spatti; Rogerio Andrade Flauzino; Luisa Helena Bartocci Liboni; Silas Fr dos Reis Alves Springer (2016) Saatavuus: Tilaustuote Kovakantinen kirja
Ivan Nunes da Silva; Danilo Hernane Spatti; Rogerio Andrade Flauzino; Luisa Helena Bartocci Liboni; Silas Fr dos Reis Alves Springer (2018) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Paulo Jorge da Silva Bartolo; Fernando Moreira da Silva; Shaden Jaradat; Helena Bartolo Taylor & Francis Ltd (2020) Saatavuus: Tilaustuote Kovakantinen kirja
Paulo Jorge da Silva Bartolo; Fernando Moreira da Silva; Shaden Jaradat; Helena Bartolo Taylor & Francis Ltd (2022) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Helena Bartolo; Paulo Jorge Da Silva Bartolo; Nuno Manuel Fernandes Alves; Artur Jorge Mateus; Henrique Amorim Almeida; Lem Taylor & Francis Ltd (2013) Saatavuus: Tilaustuote Kovakantinen kirja
Paulo de Teodoro Matos; Helena Da Silva; José Miguel Sardica Peter Lang AG, Internationaler Verlag der Wissenschaften (2019) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Licia Amazonas Calandrini Braga; Luiza Helena M Da Silva; Antonio M C Rodrigues Novas Edicoes Academicas (2018) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Fernando da Silva; Helena Maria Bártolo; Paulo Bártolo; Rita Almendra; Filipa Roseta; Henrique Amorim Almeida; Ana Lemos Taylor & Francis Ltd (2017) Saatavuus: Tilaustuote Kovakantinen kirja
Springer Sivumäärä: 307 sivua Asu: Kovakantinen kirja Julkaisuvuosi: 2016, 20.09.2016 (lisätietoa) Kieli: Englanti
This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.
