| 回声状态网络及其在图像边缘检测中的应用 |
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| 引用本文： | 裴承丹.回声状态网络及其在图像边缘检测中的应用[J].计算机工程与应用,2008,44(19):172-174. |
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| 作者姓名： | 裴承丹 |
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| 作者单位： | 中南民族大学,工商学院,计算机系,武汉,430223 |
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| 摘 要： | 循环神经网络(RNN,也称反馈神经网络)是一种重要的人工神经网络,与前馈神经网络相比具有更好的学习能力和更快的收敛速度,但其隐层结构的设计一直是个难点问题。回声状态网络(ESN)有效地解决了上述问题,相比于以前的循环神经网络,其具有结构独特、稳定性好、学习过程简单快捷等特点。介绍了回声状态网络及其学习方法,将其用于图像的边缘检测中,取得了良好的效果。
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| 关 键 词： | 回声状态网络 边界检测 统计向量 |
| 收稿时间： | 2007-9-7 |
| 修稿时间： | 2007-12-14
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Echo state networks and its application on image edge detection |
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| PEI Cheng-dan.Echo state networks and its application on image edge detection[J].Computer Engineering and Applications,2008,44(19):172-174. |
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| Authors: | PEI Cheng-dan |
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| Affiliation: | Department of Computer Science，School of Industry and Merchandise，South-Central University for Nationalities，Wuhan 430223，China |
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| Abstract: | Recurrent Neural Networks(RNN) is a kind of important artificial neural networks with better ability for learning and rate of convergence in comparison with forward neural networks,however,the design of the structure of the hidden-layer is a difficult problem all the time.Echo State Networks has no such problems with special construction,good stability,short-cut learning process.Application of ESN to the edge detection of images has been introduced after the presentation of the structure and method of learning of ESN,resulting well. |
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| Keywords: | Echo State Networks(ESN) edge detection statistical vector |
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