codebooks

与codebooks相关的网络例句 [注：此内容来源于网络，仅供参考]

The computational complexity has been reduced about 5 times over against the original one. Moreover, the interpolation and quantization processing of CW is more reasonable; 2. A secondary power normalization algorithm is proposed in this dissertation. This normalization algorithm ensures that the energy sum of SEW and REW is 1. So, the energy ratio of SEW and REW can be achieved only by using SEW energy. This ratio is applied in REW quantization and CW composition; 3. For more efficient quantization for Slowly Evolving Waveform magnitude, Rapidly Evolving Waveform magnitude and power parameters, firstly, by applying the Equivalent Rectangular Bandwidth theory, classifiable multi-codebooks method, analysis-by-synthesis approach and so on, a predictive AbS multi-codebooks SEW magnitude quantization scheme is proposed. In the scheme, pitch information is exploited to determine which codebook is searched; secondly, for REW magnitude quantization, this dissertation proposed a DCT-matrix multi-codebooks quantization scheme. The classification in muti-codebooks is based on pitch and quantized SEW power. The multi-codebooks structure may offer more the information in quantization and solve the problem of the bit requirement limits in quantization by consuming some extra storage space; Furthermore, for the switch quantization of CW gain, a new classified parameter is proposed.

本文的主要贡献体现为如下几方面：一、为了减少WI模型的计算复杂度，提出了基于快速傅立叶变换、三次B样条插值和周期延拓技术的特征波形(Characteristic Waveform，CW)表示和对齐的快速算法，与原方法相比，计算量下降到原方法的1/5，同时也使得CW在插值和量化时更合理；二、为了严格保证SEW与REW的能量和为1，提出了一种特征波形的二次功率归一化算法，仅需要SEW能量就可以算出二者的能量比，并可应用到后续的REW的分类量化和CW合成中；三、为了对慢渐变波形(Slowly Evolving Waveform，SEW)幅度、快渐变波形(Rapidly Evolving Waveform，REW)幅度和特征波形功率进行有效量化，本文首先采用临界频带理论、分析合成技术、感觉加权技术以及预测式矢量量化技术，提出了一种基于基音周期分类的SEW分析合成预测式多码书量化方法；其次，本文根据基音和量化后SEW的功率信息对REW幅度进行分类，提出了一种基于离散余弦变换的REW矩阵多码书量化方法。

In codebooks training with LBG algorithm, or iginal codebooks are generally designed with the splitting algorithm.

采用LBG算法训练码书时，初始码书的产生通常采用分裂算法。

In codebooks training with LBG algorithm, choice of original codebooks is a key technique, where the splitting algorithm is generally considered effective.

在采用LBG算法进行码书训练中，一个关键的技术就是初始码书的选取，一般认为分裂算法效果显著。