| 书目名称 | Multi-Valued and Universal Binary Neurons | | 副标题 | Theory, Learning and | | 编辑 | Igor N. Aizenberg,Naum N. Aizenberg,Joos Vandewall | | 视频video | | | 图书封面 |  | | 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 | | 关键词 | algorithms; artificial neural network; cognition; control; detection; image processing; knowledge; learning | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-3115-6 | | isbn_softcover | 978-1-4419-4978-3 | | isbn_ebook | 978-1-4757-3115-6 | | copyright | Springer Science+Business Media Dordrecht 2000 |
The information of publication is updating
|
|
发表于 2025-3-21 18:25:50
