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Titlebook: Advances in Neural Networks; Computational Intell Simone Bassis,Anna Esposito,Eros Pasero Conference proceedings 2016 Springer Internationa

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發(fā)表于 2025-3-21 19:46:01 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Neural Networks
期刊簡(jiǎn)稱Computational Intell
影響因子2023Simone Bassis,Anna Esposito,Eros Pasero
視頻videohttp://file.papertrans.cn/150/149139/149139.mp4
發(fā)行地址Dedicated to recent advances in computational and theoretical issues of artificial intelligence methods.With special emphasis on robotic applications, embedded systems, ICT computational and theoretic
學(xué)科分類Smart Innovation, Systems and Technologies
圖書封面Titlebook: Advances in Neural Networks; Computational Intell Simone Bassis,Anna Esposito,Eros Pasero Conference proceedings 2016 Springer Internationa
影響因子.This carefullyedited book is putting emphasis on computational and artificial intelligentmethods for learning and their relative applications in robotics, embeddedsystems, and ICT interfaces for psychological and neurological diseases. Thebook is a follow-up of the scientific workshop on Neural Networks (WIRN 2015)held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. Theworkshop, at its 27th edition became a traditional scientific event thatbrought together scientists from many countries, and several scientificdisciplines. Each chapter is an extended version of the original contributionpresented at the workshop, and together with the reviewers’ peer revisions italso benefits from the live discussion during the presentation...The content of book is organized in the following sections. ..1. Introduction,..2. Machine Learning,..3. Artificial Neural Networks: Algorithms and models,..4. Intelligent Cyberphysical and Embedded System,..5. Computational Intelligence Methods for Biomedical ICT in NeurologicalDiseases,..6. Neural Networks-Based Approaches to Industrial Processes,..7. Reconfigurable ModularAdaptive Smart Robotic Systems forOptoelectronics..Industry: The Whit
Pindex Conference proceedings 2016
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https://doi.org/10.1007/978-1-84628-645-2gies for choosing the weighting matrix. As an applicative example, we consider the distributed sequential algorithm for Random Vector Functional-Link networks. As expected, our experimental simulations show that the training time required by the algorithm is drastically reduced when considering a proper initialization of the weights.
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Zhichao Zheng,Yonggang Li,Ying Wangnalities and evaluation methods for modelling concepts of learning, reasoning, and data interpretation. This introductory chapter provide a brief overview on the theoretical and computational issues of such artificial intelligent methods and how they are applied to several research problems.
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Networking Models and Standards,ncluding speech discrimination, genre classification, and artist recognition. Our experimental results show that a random-vector expansion is well suited for classification tasks, achieving the best accuracy in two out of three tasks.
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2190-3018 lications, embedded systems, ICT computational and theoretic.This carefullyedited book is putting emphasis on computational and artificial intelligentmethods for learning and their relative applications in robotics, embeddedsystems, and ICT interfaces for psychological and neurological diseases. The
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