Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 黃園芳 | en_US |
dc.contributor.author | 林松山 | en_US |
dc.contributor.author | Song Sun Lin | en_US |
dc.date.accessioned | 2014-12-12T02:56:23Z | - |
dc.date.available | 2014-12-12T02:56:23Z | - |
dc.date.issued | 2006 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#GT009322513 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/79003 | - |
dc.description.abstract | 在這篇論文中,我們考慮的是二維細胞類神經網路最簡單的模板即L型模版,這份工作曾在[Lin & Yang, 2001]研究過。他們是使用building block的方式討論空間熵。而本篇論文將利用花樣生成的方式重新考慮熵的問題。有關於〝花樣生成〞的工作可參考[Ban & Lin, 2005]。當我們無法精確估計出熵時,我們使用了Connecting Operator的方法估計熵的下界。有關於〝Connecting Operator〞的工作可參考[Ban, Lin & Lin, 2006]。最後,我們將與[Lin & Yang]的結果做比較。 | zh_TW |
dc.description.abstract | In this paper, we consider the simplest two-dimensional CNN template, L-shaped template. This work had investigated on [Lin&Yang, 2001] before. They use the building block to discuss the spatial entropy. In this paper, we reappraise the spatial entropy by pattern generation method which could refer to [Ban&Lin, 2005]. When we could not evaluate the spatial entropy, we use connecting operator referred to [Ban, Lin&Lin, 2006] to evaluate the lower bounded of spatial entropy. Finally, we compare the result with [Lin&Yang]. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | 熵 | zh_TW |
dc.subject | 花樣生成 | zh_TW |
dc.subject | 細胞類神經網路 | zh_TW |
dc.subject | 模板 | zh_TW |
dc.subject | entropy | en_US |
dc.subject | pattern generation | en_US |
dc.subject | cellular neural network | en_US |
dc.subject | template | en_US |
dc.title | 二維細胞類神經網路之L型模版 | zh_TW |
dc.title | Two-Dimensional CNN with L-shaped Template | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 應用數學系所 | zh_TW |
Appears in Collections: | Thesis |
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