中英
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vector quantization中文是什么意思
- 中文翻譯
- 造句
- [網(wǎng)絡(luò)] 向量量化；矢量量化；矢量化編碼
- hvq hierarchical vector quantization 分層矢量量化
- lvq lattice vector quantization 點陣矢量量化
- lvq learning vector quantization 學(xué)習(xí)向量量化
- vq vector quantization 矢量量化，紋理壓縮（加速芯片的功能）; 紋理壓縮
- vqc vector quantization code 矢量量子化代碼
- quantization 分層量子化把連續(xù)量轉(zhuǎn)換為數(shù)字; 量化 在每個象素處，將圖像的局部特性賦予一個灰度集合中的元素的過程。數(shù)字圖象處理技術(shù)詞匯表; 量化 在每一個像素處，將圖像的局部特性賦予一個灰度集合中的元素的過程; 量化,分層,量子化; 量子化,量化(把連續(xù)量變?yōu)閿?shù)字量),整量化; 量子化；數(shù)字化；分層; 量子化作用；分層; 取離散值
- adaptive quantization 自適應(yīng)量化
- amplitude quantization 振幅量化
- binary quantization 二進制量化
- canonical quantization 二次量子化; 正則量子化
- charge quantization 電荷量子化
- conductance quantization 電導(dǎo)量子化
- differential quantization 差分量化
- digital quantization 數(shù)字量子化,數(shù)字量化
- dirac quantization 狄拉克量子化; 狄喇克量子化
- directional quantization 方向量子化
- field quantization 場量子化
- first quantization 一次量子化
- flux quantization 磁通量量子化
- geometric quantization 幾何量子化
- imaging quantization 影像量化
- macroscopic quantization 宏觀量子化
- measures of quantization 量化測量
- nonuniform quantization 非均勻量化
- phase quantization 相位量化
- In order to encode the parameters of sinusoidal model, the vector quantization techniques for amplitude parameters and the differential quantization for frequency parameters are proposed and discussed . at the same time, the frequency bin model, the random phase model and the zero phase model are also discussed
針對正弦模型參數(shù)的量化編碼，提出了幅度參數(shù)矢量量化、頻率參數(shù)差分量化等方法，并探討了頻率盒量化模型以及隨機相位和零相位模型等。 - For the objective of effective network defenses of malicious flows, this dissertation focused the deep researches of detection and control for the malicious flows, including the followings : to detect the malicious flows, the dissertation proposed the network anomaly detection approach based on the vector quantization ( vq )
本文以實現(xiàn)對惡意數(shù)據(jù)流的有效防御控制為目標(biāo),著重對網(wǎng)絡(luò)惡意數(shù)據(jù)流的檢測與控制等關(guān)鍵技術(shù)進行深入的研究,主要包括以下四個方面:對網(wǎng)絡(luò)惡意數(shù)據(jù)流進行準(zhǔn)確的檢測發(fā)現(xiàn)是惡意數(shù)據(jù)流防御的必要手段。論文首先提出了一種基于矢量量化的網(wǎng)絡(luò)異常檢測方法用于惡意數(shù)據(jù)流的檢測。 - In the paper, chapter 1 gives a comprehensive introduction of digital image compressing including its recent status, technical standards, classification in the world . chapter 2 introduces briefly the thought and ii procedure of vector quantization, describes lgb algorithm and vector quantization based on sofm neural network . chapter 3 discusses predictable coding in lossy and lossless aspects, analyzes adaptive predictable coding based on bp neural network, introduces the evaluation of algorithm on neural network in image compression . chapter 4 discusses the applications of mathematical transformation in image compression and does experiments related, analyzes the strategies of image coding in transformed domain . in chapter 5 images are decomposed and represented by wavelet transform, then discusses the characteristics and effects of wavelet functions in image compression, analyzes the wavelet coefficients after images are decomposed; based on the theories and analyses in the prior chapters, the paper presents an image compression scheme and gives results . the test results shows that the image compression scheme is practical and helpful to map into the local content of images to get rid off redundancy, so that, it can require satisfactory results of image compression
方案首先利用小波多分辨分析性質(zhì)，對圖像進行小波分解，對分解后各子圖的小波系數(shù)進行了統(tǒng)計分析，針對各子圖的小波系數(shù)特點，對不同的子圖分別采用不同的壓縮方法，低頻子圖采用基于神經(jīng)網(wǎng)絡(luò)的自適應(yīng)預(yù)測編碼，高頻子圖采用基于神經(jīng)網(wǎng)絡(luò)的矢量量化編碼，從而實現(xiàn)對圖像數(shù)據(jù)的壓縮處理。本論文第一章介紹了數(shù)字圖像壓縮處理的國內(nèi)外當(dāng)前的概況以及其技術(shù)標(biāo)準(zhǔn)和分類。在第二章，介紹了數(shù)字圖像的矢量量化技術(shù)的數(shù)學(xué)思想和過程，對lbg算法和基于sofm神經(jīng)網(wǎng)絡(luò)的矢量量化進行了闡述、分析。 - In the paper, chapter 1 gives a comprehensive introduction of digital image compressing including its recent status, technical standards, classification in the world . chapter 2 introduces briefly the thought and ii procedure of vector quantization, describes lgb algorithm and vector quantization based on sofm neural network . chapter 3 discusses predictable coding in lossy and lossless aspects, analyzes adaptive predictable coding based on bp neural network, introduces the evaluation of algorithm on neural network in image compression . chapter 4 discusses the applications of mathematical transformation in image compression and does experiments related, analyzes the strategies of image coding in transformed domain . in chapter 5 images are decomposed and represented by wavelet transform, then discusses the characteristics and effects of wavelet functions in image compression, analyzes the wavelet coefficients after images are decomposed; based on the theories and analyses in the prior chapters, the paper presents an image compression scheme and gives results . the test results shows that the image compression scheme is practical and helpful to map into the local content of images to get rid off redundancy, so that, it can require satisfactory results of image compression
方案首先利用小波多分辨分析性質(zhì)，對圖像進行小波分解，對分解后各子圖的小波系數(shù)進行了統(tǒng)計分析，針對各子圖的小波系數(shù)特點，對不同的子圖分別采用不同的壓縮方法，低頻子圖采用基于神經(jīng)網(wǎng)絡(luò)的自適應(yīng)預(yù)測編碼，高頻子圖采用基于神經(jīng)網(wǎng)絡(luò)的矢量量化編碼，從而實現(xiàn)對圖像數(shù)據(jù)的壓縮處理。本論文第一章介紹了數(shù)字圖像壓縮處理的國內(nèi)外當(dāng)前的概況以及其技術(shù)標(biāo)準(zhǔn)和分類。在第二章，介紹了數(shù)字圖像的矢量量化技術(shù)的數(shù)學(xué)思想和過程，對lbg算法和基于sofm神經(jīng)網(wǎng)絡(luò)的矢量量化進行了闡述、分析。 - Through anatomizing ezw coding algorithm and taking the effects of human being ’ s vision characteristics on quality of reconstituting image . a improved zeretrees algorithm are put forward . at last a new image compression encoding algorithm based on wavelet transform and vector quantization is put forward . the experiment show, in very low bit rate, using the proposed algorithm, the reconstructed image is superior to that of ezw in both of perception and psnr
最后,在小波樹的基礎(chǔ)上,通過對矢量量化的研究,本文提出了一種基于四叉樹結(jié)構(gòu)新的小波樹矢量量化壓縮編碼算法,實驗證明,在較高壓縮比的情況下,使用此方法得到的重構(gòu)圖象質(zhì)量(視覺效果和峰值信噪比)比通常的小波壓縮算法有了較大的提高。 - In addition, the properties and extraction methods of some common feature parameters are studied in detail . in particular, two kinds of representative features, linear prediction cepstrum coefficient ( lpcc ) and mel-frequency cepstrum coefficient ( mfcc ), are analyzed and researched on experimentation of vector quantization in text-independent speaker recognition . then, the performances of lpcc and mfcc are compared respectively on computer platform
此外,我們在說話人識別試驗中對常見的語音特征參數(shù)進行了研究,主要研究了線性預(yù)測倒譜(lpcc)、美爾倒譜(mfcc)等參數(shù),并且分別基于計算機平臺試驗比較了lpcc和mfcc參數(shù)的識別效果。 - Three commixed still image coding algorithms are proposed based on them and such ideas as : zerotree coding, wmse ( which is based on mankind visual characteristics ), classified vector quantization with different vector structures and classification methods . the chapter gives the principium analysis, realization schemes and simulation results of the proposed algorithms
在此基礎(chǔ)上，結(jié)合零樹編碼思想，以及基于人眼視覺特性和分類矢量量化的思想，根據(jù)不同的矢量構(gòu)成和分類方法提出了三種混合型靜止圖像編碼方法，給出了算法原理的分析、實現(xiàn)方案和仿真結(jié)果，最后對本章方法作出分析總結(jié)。 - In this dissertation, lots of exploratory research work has been done around some key techniques of image retrieval based on compressed-domain, which include based on discrete cosine transform ( dct ), based on vector quantization ( vq ) combine with low-level feature extraction, similarity measure and so on
本論文圍繞壓縮域圖象檢索中的一些關(guān)鍵方法，包括基于離散余弦變換和基于矢量量化等方法聯(lián)合提取圖象低層特征、圖象間相似性度的度量等技術(shù)，進行了一些探索性的研究。 - In the thesis, we select the mel-frequency cepstrum coefficients based on analyzing a lot of parameters of speech signal . mel cepstrum is of better recognition and anti-noise capability . ( 2 ) dynamic time warping, vector quantization, hidden markov model and artificial neural network can be used in speaker recognition
(2)現(xiàn)有的說話人識別方法有動態(tài)時間規(guī)整法、矢量量化法、隱馬爾可夫模型和神經(jīng)網(wǎng)絡(luò)法等，其中hmm已成為目前最佳的說話人識別處理模型。 - Then it is possible to realize high compression ratio of images . in this paper the principle of which wavelet transform can be used in images compression is discussed on basis of statistics and analysis of image's wavelet coefficients after wavelet decomposition . also some kinds of quantify and coding schemes are discussed including scalar quantization, vector quantization, embedded zerotree wavelets encodings run length coding, huffman coding and so on
論文對圖像經(jīng)分解后的小波系數(shù)進行統(tǒng)計與分析，闡述了小波變換所以能夠用于圖像壓縮的道理，并在此基礎(chǔ)上討論了多種量化和編碼方案的設(shè)計與實現(xiàn)，包括標(biāo)量量化、矢量量化、嵌入小波零樹編碼、行程編碼、哈夫曼編碼等，其中對jpeg2000采用的標(biāo)量量化和嵌入小波零樹編碼作了重點討論和分析。
- vector quantizationとは意味：ベクトル量子化｛りょうしか｝
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