lbg

This paper introduces the basic LBG arithmetic of vector quantization .

介绍了矢量量化的基本算法LBG。

Experiment performance analysis on sensitivity to initial codebook of LBG

LBG~（[1]）算法对初始码书敏感的实验性能分析

Efficient Algorithm for Reducing the Computation Redundancy of LBG Algorithm

一种减少LBG算法计算冗余量的有效改进算法

Clustering Algorithm Based on VQ and LBG in Mobile Ad Hoc Network

基于VQ和LBG的移动adhoc网络中分簇算法

Fast LBG algorithm using new codeword splitting method

使用新的码字分割方法的快速LBG算法

LBG , widely used in digital image compression , is a classical vector quantization algorithm .

LBG算法是一种经典的矢量量化算法，广泛用于数字图像的压缩。

The study of the combination of SOFM and LBG algorithm in the application of image compression

SOFM算法和LBG算法联合用于图像压缩的研究

LBG algorithm is the classical algorithm for codebook design and is foundation of other algorithms .

LBG算法是经典的码书设计算法，是各类码书设计算法的基础。

This paper proposes a codebook design method based on genetic algorithm ( GA ) and the LBG algorithm .

将遗传算法与LBG算法相结合，得到了一种矢量量化码书设计算法。

Empty Voronoi Cells Optimized Processing In LBG Algorithm

LBG算法中空包腔的优化处理

The local minimum problem is a much important factor which restricts the performance of the classic LBG algorithm .

经典LBG算法的局部极小值问题是制约其性能的重要因素。

Compared with the famous LBG algorithm , it is simple , fast and easy to comprehend .

与经典的LBG算法相比，该算法结构更简单、速度更快、更容易理解。

A Fast Improved LBG Algorithm

一种改进的LBG快速算法

The characteristic of the traditional codebook training algorithm LBG and distortion measurement are also dwelt on .

详述了传统码书训练算法LBG的特性以及训练码书的失真测度。

Next , it introduces several improved LBG algorithms : the separated means algorithm and the sorted separated means algorithm .

接着介绍了几种LBG的改进算法：分离平均算法和排序分离平均算法。

Secondly , it reduces the resolution ratio for the LBG algorithm ` s smoothing on the high frequency component .

LBG算法对高频分量有平滑效果，因此降低了分辨率；

The experimental results prove that the algorithm has better improved the expected distortion by overcoming the local optimality of LBG algorithm .

试验证明了此方法的有效性，解决了LBG算法局部最优的局限，获取更接近全局最优的码书。

A modified LBG algorithm

一个改进的LBG算法

An appropriately adapted ant colony system embedded with a simple improved LBG algorithm was proposed for vector quantization codebook design .

提出了一种基于混合蚁群算法的矢量量化码书设计算法。

A Novel Template-Training Algorithm Based on LBG and DTW

一种新的基于LBG和DTW的模板训练算法

LBG Algorithm with Equivalence Norms Generates Same Codebook

LBG算法使用等价范数产生相同码书

With three different initial codebook design methods , this paper verified the conclusion that the LBG algorithm is sensitive to the initial codebook .

指出LBG算法的缺陷，并针对LBG[1]算法对初始码书敏感这一缺陷进行分析。

Tests show that the proposed two algorithms based on the tabu search approach can greatly improve the codebook performance compared to the conventional LBG algorithm .

结果表明，基于禁止搜索的两种码书设计方案所生成的码书性能都比LBG算法有明显提高。

At last , some improved methods aimed at the defects of the sensitivity to the initial codebook of LBG algorithm are presented in the paper .

最后，针对LBG算法对初始码书敏感这一缺陷给出了一些改进方向。

The reconstructed images between the LC and the LBG algorithms have no obvious differences at the 0.375 bit / pixel condition .

在比特率为0.375bpp条件下，LC算法与LBG算法的重建图像质量无明显差别。

The traditional training algorithm for vector quantization such as the LBG algorithm uses the convergence of distortion sequence as the condition of the end of algorithm .

以LBG算法为代表的传统码书训练算法基本上都用量化失真序列收敛作算法停止条件。

This paper proves that famous LBG algorithm with equivalence norm generates same codebook if the initial codebooks are same .

证明了著名的LBG算法使用等价范数，只要初始码书相同，则产生相同码书。

The first problem , at least in the case of LBG , is that the extra capital promised is too small to deal with a serious crisis .

第一个问题，至少在劳埃德银行集团（LBG）案例中有，是预期的额外资本太少而无法应对严重危机。

Computer simulation results obtained from Gaussian distribution source and binary symmetric channels are compared with the LBG algorithm , as well as the optimum performance theoretically attainable .

在高斯独立分布信源及二进制对称信道的情况下，对该算法进行了计算机模拟，并与LBG算法及理论上的最佳性能限作了比较。

In addition , it is demonstrated to be more effective in the clustering for speech parameters and be obtained better codebook quality in comparison with LBG algorithm .

试验表明，RLS算法在语音参数聚类中表现出了很好的性能，得到的码书质量优于经典的LBG算法，从而为设计全局准最优码书提供了一种新思路。