binary quantization 中文意思是什麼
binary quantization
解釋
二進制量化- binary : adj. 二，雙，復；【化學】二元的；【數學】二進制的。n. 二，雙，復；雙體，復體；【天文學】雙[聯]星【數學】二進制。
- quantization : 分層量子化把連續量轉換為數字
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This paper can put into four parts ? this first part is the description and theoretical analyses of source coding, which focus on the research of optimizing equal quantization ? the second part presents the theoretical description of joint channel - source coding, which focus on the research of combined channel - source coding o the third part is about the application of combined channel - source coding to two different channel models, binary symmetric channel and cdma channel o in this part, two different coding designs are given according to different characters of these two channels ? and the last part is the description of simulation of combined channel - source coding ? most of my work are about two parts, one is to find the most appropriate quantization steps and centroid points of separate channel - source coding, another is to simulate the combined channel - source coding ? comparing the simulation results of separate channel - source coding and combined channel - source coding, the characters of joint channel - source coding are given
本論文可以分成四部分：第一部分給出了信源編碼的基本概念和理論分析，重點放在最優均勻量化編碼的研究方面；第二部分給出了通道?信源聯合編碼的原理敘述，重點放在復合式通道?信源編碼的分析研究上；第三部分將通道-信源聯合編碼原理應用在兩種噪聲通道上：離散無記憶通道和cdma通道，並根據兩種通道的不同特點詳細描述了兩種相應的編碼設計方案；第四部分給出了復合式通道-信源編碼的模擬結果以及對結果的相應分析。 -
Chebyshev map is a one ? imension chaotic map which has simple iteration equation easy to be realized, and extremely sensitive on initial conditions, in this thesis we use various quantization functions to generate binary sequences for ds ? s and multilevel sequences for fh ? s
Chebyshev混沌映射是一種一維混沌映射，其迭代方程簡單，易於實現，且對初始值極其敏感。本文通過不同的量化函數得到直擴序列和跳頻序列。 -
The paper analyzes binary - split gradient & threshold initial codebook generation - algorithms, codebook generation algorithms based on kohonen self - organizing feature map neural network, a fast codeword searching algorithm using l2 - norm pyramid data structure, side - match vector quantization algorithms, and a fuzzy classified vector quantization algorithm, systematicly explores their application to image compression, computer simulation results show that they are practical and efficient
文中重點分析了二元分裂梯度與閾值初始碼書生成演算法、基於kohonen自組織特徵映射神經網路的碼書生成演算法、基於l2范數金字塔數據結構的快速碼字搜索演算法、邊緣匹配矢量量化演算法、模糊分類矢量量化演算法，系統地研究了它們在圖像壓縮編碼中的應用，並進行了計算機模擬，實驗結果表明這些演算法是實際有效的。
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