本文提出了一种利用语音信号分布特性的矢量量化方法。
A new approach which exploits the distribution properties of speech signal for vector quantization of speech signal is proposed in the paper.
为了降低误差积累的影响，本文提出了一种新型的矢量量化方法。
In this paper, a new scheme of vector quantization is described to reduce the effect of error propagation.
文章介绍一种图像低频子带编码的矢量量化方法—非对称树结构矢量量化。
One of VQ image coding method used in the low frequency subband-the unbalanced tree-structured VQ is presented in this paper.
最后，针对几何分布不规则的一般信源，给出一般的几何矢量量化方法———标量矢量量化(SVQ)。
Finally, a more useful geometric vector quantization method is presented, which is called scalar vector quantization (SVQ).
针对这些问题，基于最小化学习误差的增量思想，该文将学习型矢量量化（LVQ）和生长型神经气（GNG）结合起来提出一种新的增量学习型矢量量化方法，并将其应用到文本分类中。
To solve these problems, based on minimizing the increment of learning errors and combining LVQ and GNG, the authors propose a new growing LVQ method and apply it to text classification.
作为图像有损压缩的方法之一，矢量量化的压缩比极大。
As one method of image lossy compression vector quantization has great compression ratio.
图像压缩是数字图像处理中最重要的关键技术之一，传统的图像压缩方法有预测编码、变换编码和矢量量化等。
Image compression is one of the most important key techniques in image processing. Traditional compression methods include prediction coding, transform coding and vector quantization (VQ).
矢量量化(VQ)是语音识别中广泛应用的一种数据压缩和编码方法。
Vector Quantization (VQ) is one of popular data compression and data coding methods for speech recognition at present.
本文对目前流行的各种方法进行了归类，主要思想有：边缘保持、矢量量化、小波变换、插值核、分形技术以及边缘模型。
And this paper classifies the popular methods, the main ideas are as follows: edge preserving, vector quantization, wavelet transform, interpolation kernel, Fractal technology and edge model.
将学习矢量量化神经网络集成在基于实例推理的故障诊断方法中，减小了实例搜索空间，提高了实例检索效率。
The learning vector quantization neural network has been integrated successfully with the case-based reasoning approach to reduce the case indexing space and to enhance the indexing efficiency.
本文给出了一种新的图像矢量量化码书的优化设计方法——粒子对算法。
This paper presents a new strategy of particle-pair(PP) for vector quantization(VQ) in image coding.
提出了一种将改进的FCM聚类算法与矢量量化相结合的说话人识别的方法。
A speaker recognition method based on improved FCM clustering with vector quantization is introduced in this paper.
本文提出了基于改进禁止搜索(TS)算法的矢量量化(VQ)码书设计方法。
Codebook design algorithms based on tabu search (TS) approach are presented for vector quantization (VQ).
作为特征签名在重复图像检测方面的应用，基于多特征签名的重复图像检测方法改进了矢量量化过程中的编码映射方式。
As another application of feature signature, multi-signature based duplicate image detecting method improved the mapping and encoding during vector quantization.
矢量量化(VQ)方法是文本无关说话人识别中广泛应用的建模方法之一，它的主要问题是码本设计问题。
Vector Quantization (VQ) is one of the popular codebook design methods for text-independent speaker identification. The key problem of VQ is the design of codebook.
该方法是以分块截断编码技术和矢量量化技术为基础的编码方法。
This method is based on the techniques of block truncation coding and vector quantization.
由于该方法把分形和矢量量化编码结合起来，因此解码时只需查找码书，并仅进行对比度变换。
This method connects fractal and vector quantization coding together, during the process of decoding, the only need to check the codebook and to transform the contrast.
提出了语音谱参数的切换双预测多级矢量量化算法(DPMSVQ)的码本设计方法。
A codebook design method for a switched dual predictive multi stage vector quantization (DPMSVQ) scheme of LPC parameters.
结合动态谱特性的语音识别研究，阐述了一种有限状态矢量量化(FSVQ)方法。
A speech recognition method is described, that is based on a combination of finite-state vector quantization (FSVQ) and dynamic spectral features.
文章提出了语音谱参数的增强双预测多级矢量量化算法(EDPMSVQ)的码本设计方法。
This paper presents a codebook design method of an enhanced dual predictive multi-stage vector quantization (EDPMSVQ) scheme for LPC parameters.
本文提出了一种基于分类矢量量化器的小目标红外图像的压缩方法。
This paper presents a small target infrared image compression scheme based on classified vector quantization.
最后本文探讨了一种将基于结构特征的自适应分块与矢量量化相结合的编码方法。
At last, the adaptive vector quantization coding based on the DCT spectrum main orientation mentioned above is developed.
用不同语音参数进行实验，实验表明应用矢量量化的方法用在说话人识别中是一种有效方法。
The experiment of using different phonetic parameter indicates that the VQ algorithm is an effective method in speaker recognition.
针对边缘匹配矢量量化图像编码方法存在的出轨现象，提出一种引入支持向量机的方法。
To tackle the derailment phenomenon consisting in side-match vector quantization image coding technology, we introduced support vector machine.
根据准周期性的韵母相邻周期具有很强相关性的特点，本文提出一种分别对声母和韵母采取不同维数的矢量量化的方法。
This paper presents a new VQ method with different dimensions to vowels and consonants based on the quasi - periodicity of neighbour vowels which leads to strong correlations.
该文提出了一种将模糊C -均值聚类法的各种改进算法与矢量量化法相结合的说话人辨认的新方法。
Several new algorithms of fuzzy C-mean clustering with the combination of vector quantization are proposed for speaker identification.
矢量量化（VQ）方法是文本无关说话人识别中广泛应用的建模方法之一，它的主要问题是码本设计问题。
Vector Quantization(VQ)is one of the popular codebook design methods for text-independent speaker identification.
仍然有些算法很容易就可以被归入好几个类别，好比学习矢量量化，它既是受启发于神经网络的方法，又是基于实例的方法。
There are still algorithms that could just as easily fit into multiple categories like Learning Vector Quantization that is both a neural network inspired method and an instance-based method.
提出利用主元分析（PCA）和学习矢量量化神经网络（LVQ）相结合的方法进行人脸识别。
This paper proposes a face recognition method based on PCA and LVQ neural networks.
提出利用主元分析（PCA）和学习矢量量化神经网络（LVQ）相结合的方法进行人脸识别。
This paper proposes a face recognition method based on PCA and LVQ neural networks.
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