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Titlebook: Multi-Valued and Universal Binary Neurons; Theory, Learning and Igor N. Aizenberg,Naum N. Aizenberg,Joos Vandewall Book 2000 Springer Scien

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書目名稱Multi-Valued and Universal Binary Neurons
副標題Theory, Learning and
編輯Igor N. Aizenberg,Naum N. Aizenberg,Joos Vandewall
視頻videohttp://file.papertrans.cn/641/640038/640038.mp4
圖書封面Titlebook: Multi-Valued and Universal Binary Neurons; Theory, Learning and Igor N. Aizenberg,Naum N. Aizenberg,Joos Vandewall Book 2000 Springer Scien
描述.Multi-Valued and Universal Binary Neurons. deals with twonew types of neurons: multi-valued neurons and universal binaryneurons. These neurons are based on complex number arithmetic and arehence much more powerful than the typical neurons used in artificialneural networks. Therefore, networks with such neurons exhibit a broadfunctionality. They can not only realise threshold input/output mapsbut can also implement any arbitrary Boolean function. Two learningmethods are presented whereby these networks can be trained easily.The broad applicability of these networks is proven by several casestudies in different fields of application: image processing, edgedetection, image enhancement, super resolution, pattern recognition,face recognition, and prediction. The book is hence partitioned intothree almost equally sized parts: a mathematical study of the uniquefeatures of these new neurons, learning of networks of such neurons,and application of such neural networks. Most of this work wasdeveloped by the first two authors over a period of more than 10 yearsand was only available in the Russian literature. With this book wepresent the first comprehensive treatment of this important class
出版日期Book 2000
關(guān)鍵詞algorithms; artificial neural network; cognition; control; detection; image processing; knowledge; learning
版次1
doihttps://doi.org/10.1007/978-1-4757-3115-6
isbn_softcover978-1-4419-4978-3
isbn_ebook978-1-4757-3115-6
copyrightSpringer Science+Business Media Dordrecht 2000
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eurons, learning of networks of such neurons,and application of such neural networks. Most of this work wasdeveloped by the first two authors over a period of more than 10 yearsand was only available in the Russian literature. With this book wepresent the first comprehensive treatment of this important class 978-1-4419-4978-3978-1-4757-3115-6
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https://doi.org/10.1007/978-1-4757-3115-6algorithms; artificial neural network; cognition; control; detection; image processing; knowledge; learning
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978-1-4419-4978-3Springer Science+Business Media Dordrecht 2000
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The Carbohydratesoms having many hydroxyl (alcohol) groups and either a ketone group or an aldehyde group. Typically, each carbon atom that does not bear an aldehyde or ketone group (collectively called carbonyl groups) will have a hydroxyl group. Simple sugars may be strung together in chains to form long polymers.
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