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G.723语音编码介绍及优化 语音编码分成波形编码、参数编码和混合编码.波形编码就是语音信号形成的波形进行处理和加工，参数编码是以语音信号产生的数字模型为基础，求出其模型参数，然后按照这些参数还原数字模型，合成语音。混合编码是综合了波形编码和参数编码的长处，在4－16kbps的速率上进行高质量的语音合成。例如多脉冲激励线性预测编码(MPLPC),码本激励线性预测编码(CELP)都是混合编码。-G.723 speech coding and optimization of voice introd
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CELP
The most common Speech coding scheme is Code-Excited Linear Predictive (CELP) coding, which is used for example in the GSM standard. In CELP, the modelling is divided in two stages, a linear predictive stage that models the spectral envelope a
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This function synthesizes a (speech) signal based on a LPC (linear-
％ predictive coding) model of the signal. -This function synthesizes a (speech) sign al based on a LPC (linear-% predictive coding) m odel of the signal.
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This function synthesizes a (speech) signal based on a LPC (linear-
％ predictive coding) model of the signal.-This function synthesizes a (speech) signal based on a LPC (linear- predictive coding) model of the signal.
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单输入单输出模型预测控制算法实现--一般实现，逆响应和线性规划-SISO model predictive control- a general approach, inverse response and linear programming
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OTOMATİ K KONUŞ MA TANIMA ALGORİ TMALARININ UYGULAMALARI
Kö ksal Ö CAL
Ankara Ü niversitesi
Fen Bilimleri Enstitüsü
Elektronik Mühendisliğ i Anabilim Dalı
Danı ş man : Yrd. Doç . Dr. H. Gö kh
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Levison-Durbin 语音信号处理中的线性预测编码LPC 理论、格型滤波器以及求解现行预
测方程的算法，可以实现对语音信号重要元素的分析、合成甚至识别。
基于现有的实验平台，我们可以利用 Matlab 函数来获得几个固定语音元素（如元音）
的模型系数，LPC 得到的系数组成 IIR 滤波器。利用冲击脉冲
序列作为输入，我们就可以得到原来的语音。这是一种简单的语音合成功能。-Levison-Durbin speech signal processing in li
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Developing Models from Experimental Data using System Identification Toolbox-1. webinar_walk_through.m: contains all the linear and nonlinear estimation examples presented during the webinar.
2. Data files and Simulink models: process_data.mat,
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for linear induction motor drive using model predictive control
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介绍线性预测编码(LPC)及其基本原理，由语音信号常用的全极点模型的传递函数推导出线性预测方程，-Introduction of linear predictive coding (LPC) and the basic principles of commonly used by the speech signal transfer function of all-pole model of a linear prediction equation is derived,
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matlab语音信号处理工具箱
本工具箱可配合语音数据库使用，用于计算线性预测语音模型的参数，语音声调转换，语音自动解析分解，语音语速变换及更改发音的重音，音量，清晰度等。配套图书《Speech Processing and Synthesis Toolboxes》已经出版，翻译进行中-matlab signal processing toolbox with the voice of the Toolbox database can be used for calculating line
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将原语音文件进行分析解码，用全极点模型，通过线性系统预测进行声音的合成和编码。-Original voice file for analysis by linear system predictive decoding, with the all-pole model, the sound synthesis and coding.
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Model Predictive Control based on linear models is widely used in the process Industry.
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（1）掌握线性预测分析的基本原理。
（2）掌握线性预测误差滤波器参数与语音信号声道模型参数之间的关系。
（3）熟练掌握线性预测分析的自相关方法和Levinson-Durbin递推算法。
（4）熟悉语音信号的LPA谱估计方法-1) master the basic principles of linear predictive analysis.
(2) to master the linear prediction error filter parameters and voic
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采用线性预测分析不仅能够得到语音信号的预测波形，而且能够提供一个非常好的声道模型(The linear predictive analysis can not only predict the waveform of the speech signal, but also provide a very good vocal tract model)
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对线性时变模型和非线性模型的预测控制算法进行了仿真分析，设计了两种模型下的模型预测控制的实现(Simulation analysis of linear time-varying model and nonlinear model predictive control algorithm)
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