| 书目名称 | Neural Networks in Multidimensional Domains |
| 副标题 | Fundamentals and New |
| 编辑 | Paolo Arena,Luigi Fortuna,Maria Gabriella Xibilia |
| 视频video | |
| 概述 | The first argument of its kind to be published.Has multidisciplinary appeal for students in related areas.The content, layout and price are ideal for graduates and students |
| 丛书名称 | Lecture Notes in Control and Information Sciences |
| 图书封面 |  |
| 描述 | In this monograph, new structures of neural networks in multidimensional domains are introduced. These architectures are a generalization of the Multi-layer Perceptron (MLP) in Complex, Vectorial and Hypercomplex algebra. The approximation capabilities of these networks and their learning algorithms are discussed in a multidimensional context. The work includes the theoretical basis to address the properties of such structures and the advantages introduced in system modelling, function approximation and control. Some applications, referring to attractive themes in system engineering and a MATLAB software tool, are also reported. The appropriate background for this text is a knowledge of neural networks fundamentals. The manuscript is intended as a research report, but a great effort has been performed to make the subject comprehensible to graduate students in computer engineering, control engineering, computer sciences and related disciplines. |
| 出版日期 | Book 1998 |
| 关键词 | MATLAB; algorithms; control; control engineering; learning algorithm; modeling; neural networks; robotics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/BFb0047683 |
| isbn_softcover | 978-1-85233-006-4 |
| isbn_ebook | 978-1-84628-527-1Series ISSN 0170-8643 Series E-ISSN 1610-7411 |
| issn_series | 0170-8643 |
| copyright | Springer-Verlag London 1998 |
发表于 2025-3-21 17:56:39
