A new multi-stage vector quantizer (MSVQ) of line spectral frequency parameters is designed.
设计了一种新的线谱频率参数多级矢量量化编码方案。
Finally, a series of inequalities is derived, which gives a quantitative relation between the performance of a vector quantizer and rate-distortion function.
最后，导出了反映矢量量化器工作特性和率失真函数之间的数量关系的不等式串。
Moreover, a predictive phase vector quantizer is proposed in this thesis based on the above method. The synthesis speech is slightly improved for female speakers.
此外，本文在此基础上提出了一种相位预测式矢量量化方案，使得女声的语音合成质量有所改进。
The Counterpropagation Network (CPN) can be applied to image compression as a vector quantizer. However, the CPN learning algorithm has two obvious disadvantages in codebook designing.
对向传播神经网络(CPN)可以作为矢量量化器用于图像压缩，但CPN学习算法在进行码书设计时存在两个明显的缺陷。
The Counterpropagation Network (CPN) can be applied to image compression as a vector quantizer. However, the CPN learning algorithm has two obvious disadvantages in codebook designing.
对向传播神经网络(CPN)可以作为矢量量化器用于图像压缩，但CPN学习算法在进行码书设计时存在两个明显的缺陷。
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