最大細劃分值 的英文怎麼說
中文拼音 [zuìdàxìhuàfēnzhí]
最大細劃分值
英文
maximum subdivisions levels- 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
- 細 : 形容詞1 （條狀物橫剖面小） thin; slender 2 （顆粒小） in small particles; fine 3 （音量小） thin ...
- 劃 : 劃動詞1 （撥水前進） paddle; row 2 （合算） be to one s profit; pay 3 （用尖銳的東西在別的東西上...
- 分 : 分Ⅰ名詞1. （成分） component 2. （職責和權利的限度） what is within one's duty or rights Ⅱ同 「份」Ⅲ動詞[書面語] （料想） judge
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This thesis explains the necessity of the character recognition technology of the computer at first, describe the meaning in which the handwritten numeral discerns ; pretreatment technology of handwritten numeral recognition, including two value, line segmentation, word segmentation smooth, removing noising, standardization and thinning are discussed two value concretely discusses whole threshold value, some threshold value, dynamic threshold value and utilize space information to carry on threshold, which are several kinds of common method of choosing threshold value, especially utilize space information to carry on threshold value is describe in detail ; adopting to the foundation of thinning based on mathematics morphology, thinning algorithm of serials same and thinning algorithm of protecting shape are discussed ; afterwards, according to principle ' s diagram of the on - line character recognition, by analyzing the structure feature of the handwritten numeral, this thesis has proposed the online recognition te chnology of the free handwritten numeral based on the stroke feature and the online recognition technology of the free handwritten numeral based on the multistage classifying device. detail narrated noise removing, stroke characteristic definition and discernment, distance criterion of whole word match ; then under the foundation of handwritten numeral segmentation, off - line handwritten numeral recognition is researched. especially minimum distance classifying device, tree classifying device and adaptive resonance ( art ) network classifying device is discussed at the same time, believes degree analyses are introduced to integrate a lot of classifying devices ; at the end, the typical application of the handwritten numeral recognition was briefly narrated, its application in extensive data statistics, financial affairs, tax, finance and mail sorting have been explored
二值化時對整體閾值二值化、局部閾值二值化、動態閾值二值化和利用空間信息進行閾值選取幾種常用的閾值選取方法進行討論，特別對利用空間信息進行閾值選取進行了詳細論述；在對通過對基於數學形態學的細化的基礎上，討論序貫同倫形態細化演算法和保形的快速形態細化演算法；然後依據聯機字元識別原理框圖，分析了手寫數字的結構特點，提出了基於筆劃特徵的任意手寫數字在線識別技術和基於多級分類器任意手寫數字在線識別技術，對其中涉及的筆劃識別前的噪聲處理、筆劃間特徵量的定義及識別、整字匹配的距離準則進行了詳細敘述；繼而在對手寫數字的分割的基礎下對脫機手寫數字識別進行了研究，對基於最小距離分類器字元識別、基於樹分類器的字元識別、基於自適應共振（ art ）網路的字元識別分別進行了詳細討論，並引入置信度分析將多個分類器進行了混合集成；最後簡單闡述了手寫數字識別的典型應用，對其在大規模數據統計、財務、稅務、金融及郵件分揀中的應用進行了探索。The beginning point of the first research direction is that we design a type of load - balancing virtual topology which is insensitive to the traffic, such plan method has been proposed whose name is vlbs ( valiant load - balancing schemem ), the disadvantage of vlbs is that it can only be applied to the homogeneous network in which each node has the same capacity, in chapter2, a more general valiant load - balancing scheme ( gvlbs ) has been proposed, the advantage of the gvlbs is that it can be used both on the homogeneous network and heterogeous network, in this chapter, we will give the detail derivation process and numerical analysis. the beginning point of the second research direction is that we first design a virtual topology for the physical topology under a specific traffic matrix, for a while, the traffic has changed, the network performence will decline. under such condition, in chpater 3, a virtual topology reconfiguration algorithm is studied which can decrease the average weighted hops
本文針對動態變化業務量情況下的wdm網路設計方法劃分為兩個主要的研究方向，第一個方向的研究出發點是可以在最初的虛拓撲設計過程中根據物理拓撲情況設計出一種虛拓撲出來，該虛拓撲是負載均衡的，在這種虛拓撲上跑的業務量矩陣特徵只要在某種范圍以內，無論它怎樣動態變化，網路都不會出現擁塞，但這種虛拓撲設計演算法vlbs的一個缺陷是它只能適用於同構網路，即每個節點所擁有的容量大小都相等，在第二章中，本文提出了一種更通用的負載均衡的光網路虛拓撲設計演算法gvlbs ，該演算法與傳統的負載均衡演算法vlbs不同之處在於vlbs演算法只能適用於同構網路而gvlbs演算法既可以適用於同構網路，又可以適用於異構網路，在本章中將給出了gvlbs演算法的的詳細推導和數值分析。
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