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引用次数: 24

摘要

提出了Kohonen自组织图的新扩展,称为塑料自组织图(PSOM)。PSOM不同于任何其他网络,因为它只有一个运行阶段。PSOM在测试前不像SOM及其变体那样经过训练周期。因此,每个模式在任何时候都被视为相同的。该算法使用图结构来表示数据,并可以添加或删除神经元来学习动态非平稳模式集。该网络在实际雷达应用和人工非平稳问题上进行了测试。
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The plastic self organising map
A novel extension to Kohonen's self-organising map, called the plastic self organising map (PSOM), is presented. PSOM is unlike any other network because it only has one phase of operation. The PSOM does not go through a training cycle before testing, like the SOM does and its variants. Each pattern is thus treated identically for all time. The algorithm uses a graph structure to represent data and can add or remove neurons to learn dynamic nonstationary pattern sets. The network is tested on a real world radar application and an artificial nonstationary problem.
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