So, how to achieve global optimal codebook become the one of key problems of designing VQ algorithm.
因此，如何获得全局最优的码书成为矢量量化算法设计的主要研究问题之一。
The experiment of using different phonetic parameter indicates that the VQ algorithm is an effective method in speaker recognition.
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。
VQ Model Based on Clustering Validity Analysis: it's the flaw for the codebook training algorithm that the size of codebook is choosed artificially.
基于聚类有效性分析的VQ模型：VQ模型电码本的训练算法有一个弱点：电码本大小是人为指定的。
Now we introduce trajectory model in speaker recognition and improve the codebook training algorithm for VQ.
文章把轨线模型应用于说话人识别，同时对VQ模型的电码本训练算法进行了改进。
Base on it, a new fast VQ search algorithm using Energy Band Segmentation is presented, which is recommended in the actual satellite codec system.
以此为研究背景，提出了一种新的基于能量分级的快速VQ搜索算法，并应用于实际卫星编解码系统中。
The algorithm of VQ must be improved to reducing amount of calculation, increasing compression rate and steadying the quality of rebuilt image at same time.
通过对矢量量化图像编码算法进行改进，达到低运算量，高压缩比以及稳定的图像质量的目的。
This paper presents a continuous VQ clustering (CVQC) algorithm for realtime speech recognition, which incorporates the temporal information of speech into both training and recognition processes.
本文阐述了一个用于实时语声处理的连续矢量量化聚算法(CVQC)。该算法把语声信息的时变性质用于训练和识别过程。
An evolutionary algorithm based channel-optimized VQ (COVQ) design algorithm on noisy channel is presented in the paper.
本文提出了一个基于进化算法的信道最优矢量量化器(COVQ)设计算法。
An optimized VQ codebook design algorithm of image compression is introduced in this paper.
提出了一种针对码书优化的图像矢量量化算法。
This paper presents systematically fast search algorithms in VQ, and an efficient search algorithm is introduced.
本文系统地总结了矢量量化中的快速搜索算法，并在此基础上给出了一种有效的快速算法。
The evolutionary algorithm is introduced into the design of COVQ to achieve a significant improvement of VQ performance for a given noisy channel status model.
该算法在给定信道状态模型和存在信道噪声的情况下，可以有效地提高矢量量化器的性能，实现了信道最优矢量量化器的设计。
The algorithm achieves a significant improvement of COVQ performance for a given noisy channel status model over other conventional VQ design methods, as confirmed by experimental results.
采用该算法，在给定信道状态模型和信道噪声情况下，可有效地提高矢量量化器的性能，仿真实验结果表明该算法可获得比传统算法更优的性能增益。
The algorithm achieves a significant improvement of COVQ performance for a given noisy channel status model over other conventional VQ design methods, as confirmed by experimental results.
采用该算法，在给定信道状态模型和信道噪声情况下，可有效地提高矢量量化器的性能，仿真实验结果表明该算法可获得比传统算法更优的性能增益。
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