• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >Competitive Dynamics and Pattern Formation in a Large Array of Opto-electronic Feedback Circuit System
【24h】

Competitive Dynamics and Pattern Formation in a Large Array of Opto-electronic Feedback Circuit System

机译：大型光电反馈电路系统中的竞争动力学和图形形成

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In artificial neural networks (ANN) individual nodes are used as processing units that perform simple computations. The computations can be performed based on unsupervised or supervised learning schemes. One type of learning scheme is a competitive unsupervised approach. In the competitive approach different nodes compete to become the "winner(s)", representing the highest activity level. In a large array opto-electronic system the competitive dynamics is not restricted to single elements but is some specially distributed structure. This interaction is typical for partially distributed nonlinear systems with complex behavior but may be unusual behavior in other systems with large arrays of elements for example some ANN. With an opto-electronic system it may be possible to consider new dynamics and more complex behavior for systems with large arrays. A different approach for parallel high resolution information processing that potentially goes beyond processing large numbers of neurons or elements is considered. NN has been successful in processing low-resolution images. Hopefully opto-electronic systems can generate similar mechanisms seen in NN such as cooperation and competition. Perhaps different self-organizing structures or patterns generated by these systems have some features similar to competition and cooperation. These types of structure or pattern interactions can be possible building blocks for more robust computational processes.
机译：在人工神经网络（ANN）中，单个节点用作执行简单计算的处理单元。可以基于无监督或有监督的学习方案来执行计算。一种学习方案是竞争性无监督方法。在竞争方法中，不同的节点竞争成为“赢家”，代表最高的活动水平。在大型阵列光电系统中，竞争动力学不仅限于单个元素，而是一些特殊分布的结构。对于具有复杂行为的部分分布的非线性系统来说，这种相互作用是典型的，但在具有大量元素数组的其他系统（例如某些ANN）中，这种相互作用可能是异常的。对于光电系统，对于具有大阵列的系统，可以考虑新的动力学特性和更复杂的行为。考虑了一种并行的高分辨率信息处理的不同方法，该方法可能超出了处理大量神经元或元素的范围。 NN已成功处理低分辨率图像。希望光电系统可以产生类似NN的机制，例如合作与竞争。这些系统生成的不同的自组织结构或模式也许具有类似于竞争与合作的特征。这些类型的结构或模式交互可能是更健壮的计算过程的构建基块。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号