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Titlebook: Neural Nets WIRN Vietri-99; Proceedings of the 1 Maria Marinaro,Roberto Tagliaferri Conference proceedings 1999 Springer-Verlag London Limi

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發(fā)表于 2025-3-21 16:42:57 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Neural Nets WIRN Vietri-99
副標(biāo)題Proceedings of the 1
編輯Maria Marinaro,Roberto Tagliaferri
視頻videohttp://file.papertrans.cn/664/663679/663679.mp4
叢書(shū)名稱(chēng)Perspectives in Neural Computing
圖書(shū)封面Titlebook: Neural Nets WIRN Vietri-99; Proceedings of the 1 Maria Marinaro,Roberto Tagliaferri Conference proceedings 1999 Springer-Verlag London Limi
描述From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains a selection of papers from WIRN Vietri-99, the 11th Italian Workshop on Neural Nets. This annual event, sponsored, amongst others, by the IEEE Neural Networks Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of topics within neural networks, including pattern recognition, signal and image processing, mathematical models, neuro-fuzzy models and economics applications.
出版日期Conference proceedings 1999
關(guān)鍵詞Support Vector Machine; algorithms; classification; cognition; computational intelligence; control; filter
版次1
doihttps://doi.org/10.1007/978-1-4471-0877-1
isbn_softcover978-1-4471-1226-6
isbn_ebook978-1-4471-0877-1Series ISSN 1431-6854
issn_series 1431-6854
copyrightSpringer-Verlag London Limited 1999
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沙發(fā)
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978-1-4471-1226-6Springer-Verlag London Limited 1999
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Neural Nets WIRN Vietri-99978-1-4471-0877-1Series ISSN 1431-6854
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Polynomial Clusterons Exhibit Statistical Estimation AbilitiesThe aim of this paper is to investigate the behavior of neural clusterons that learn in an unsupervised fashion by means of an information-theoretic based rule. Particularly the aim is to investigate on the clusteron’s statistical estimation abilities that naturally emerge from their learning behaviors.
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發(fā)表于 2025-3-22 14:15:03 | 只看該作者
Theory, Implementation, and Applications of Support Vector Machinescal properties of SVMs, then present an implementation of SVMs able to work with training sets of very large size. Finally, we discuss two computer vision applications in which SVMs for both pattern recognition and regression estimation have been successfully employed.
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On Sequential Bayesian Logistic Regressionn Model sequentially. A Gaussian probability density over the parameters of the Logistic model is propagated on a sample by sample basis. Two other approaches, the Laplace Approximation and the Variational Approximation are compared with the state space formulation. Features of the latter approach,
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Simple Reverberations and the Mindrations [1]. In Part I, a preliminary description is given as to how such reverberations can be created, held and annihilated in a controlled manner. A discussion is then given, in Part II, of the nature of, and problems associated with, modelling the frontal lobes. In particular the manner they may
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Computational Intelligence in Hydroinformatics: A Reviewon with the aquatic environment. Many new modeling techniques have been entered in Hydroinformatics successfully. Among them, the application Computational Intelligence methods in Hydroinformatics is a relatively new area of research, even if some successful results have been already obtained. In th
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