Vector quantization (VQ) is an efficient data compression technique.
矢量量化(VQ)是一种有效的数据压缩技术。
Vector quantization (VQ) is an efficient approach of lossy data compression.
矢量量化(VQ)是一种高效的有损压缩技术。
This paper presents a new strategy of particle-pair(PP) for vector quantization(VQ) in image coding.
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。
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).
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。
Codebook design algorithms based on tabu search (TS) approach are presented for vector quantization (VQ).
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。
Self-organizing neural network is a very efficient method for pattern recognition and vector quantization(VQ).
为有效提高矢量量化码书的性能和学习效率，需进一步改进自组织神经网络的学习算法。
In this article, a new ECG compression method applying 2-step vector quantization (VQ) on DCT coefficients of ECG data was introduced.
本研究提出了一种新的心电信号压缩方法，该方法对心电数据进行离散余弦变换(DCT)并对DCT变换的结果进行二级矢量量化。
Vector quantization (VQ) is always more powerful than scalar quantization in theory.
在理论上上矢量量化的性能总是优于标量量化。
Vector Quantization (VQ) is one of popular data compression and data coding methods for speech recognition at present.
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 the popular codebook design methods for text-independent speaker identification. The key problem of VQ is the design of codebook.
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.
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。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
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