Convert linear prediction coefficients to cepstral coefficients or cepstral coefficients to linear prediction coefficients - Simulink

描述

从cepstral系数块中的LPC将线性预测系数（LPC）转换为CEPSTRAL系数（CCS），或将CEPSTRAL系数转换为线性预测系数。设置转换类型parameter toLPCs to cepstral coefficients或者Cepstral coefficients to LPCsto select the domain into which you want to convert your coefficients. The LPC port corresponds to LPCs, and the CC port corresponds to the CCs. For more information, seeAlgorithm。

块输入可以是N-经过-Mmatrix or an unoriented vector. Each column of the matrix is treated as a channel. When the input is an unoriented vector, the input is treated as one channel.

Consider a signalx(n) as the input to an FIR analysis filter represented by LPCs. The output of this analysis filter,e(n), is known as the prediction error signal. The power of this error signal is denoted by P, the prediction error power.

当您选择时LPCs to cepstral coefficients来自转换类型列表中,您可以指定the prediction error power in two ways. From theSpecify Plist, choosevia input portto input the prediction error power using input port P. The input to the port must be a vector with length equal to the number of input channels. Select假设P等于1to set the prediction error power equal to 1 for all channels.

当您选择时LPCs to cepstral coefficients来自转换类型list, the输出尺寸与输入大小相同出现复选框。选择此复选框时，LPC的输入向量的长度等于CCS的输出向量。当您不选择此复选框时，请输入Length of output cepstral coefficientsparameter.

当您选择时LPCs to cepstral coefficients来自转换类型列表，您可以使用If first input value is not 1当LPC向量的第一个系数不为1时，参数指定块的行为。

Replace it with 1—- Changes the first value of the coefficient vector to 1. The other coefficient values are unchanged.
归一化- 将整个系数向量除以第一个系数，以使LPC矢量的第一个系数为1。
归一化and Warn- 将整个系数向量除以第一个系数，以使LPC矢量的第一个系数为1。The block displays a warning message telling you that your vector of coefficients has been normalized.
错误— Displays an error telling you that the first coefficient of the LPC vector is not 1.

当您选择时Cepstral coefficients to LPCs来自转换类型list, theOutput Pcheck box appears on the block. Select this check box when you want to output the prediction error power from output port P.

Algorithm

The cepstral coefficients are the coefficients of the Fourier transform representation of the logarithm magnitude spectrum. Consider a sequence,x(n), having a Fourier transformX(ω). The cepstrum,c_x(n), is defined by the inverse Fourier transform ofC_x(ω), whereC_x(ω) = log_eX(ω)。有关计算时间域信号计算CEPSTRUM系数的信息，请参见真正的Cepstrum块参考页面。

LPC to CC

When in this mode, this block uses a recursion technique to convert LPCs to CCs. The LPC vector is defined by $[\begin{matrix} a_{0} & a_{1} & a_{2} & \begin{matrix} 。。。 & a_{p} \end{matrix} \end{matrix}]$ CC向量由 $[\begin{matrix} c_{0} & c_{1} & c_{2} & 。。。 & c_{p} & 。。。 & c_{n - 1} \end{matrix}]$ 。递归由以下等式定义：

$c_{0} = {日志}_{e} P$

$c_{m} = - a_{m} + \frac{1}{m} \sum_{k = 1}^{m - 1} [- (m - k) \cdot a_{k} \cdot c_{(m - k)}], 1 \leq m \leq p$

$c_{m} = \sum_{k = 1}^{p} [\frac{- (m - k)}{m} \cdot a_{k} \cdot c_{(m - k)}], p < m < n$

CC至LPC

在此模式下，此块使用递归技术将CCS转换为LPC。CC向量由 $[\begin{matrix} \begin{matrix} c_{0} & c_{1} & c_{2} & 。。。 \end{matrix} & c_{p} & 。。。 & c_{n} \end{matrix}]$ LPC向量由 $[\begin{matrix} a_{0} & a_{1} & a_{2} & \begin{matrix} 。。。 & a_{p} \end{matrix} \end{matrix}]$ 。递归由以下方程定义

$a_{m} = - c_{m} - \frac{1}{m} \sum_{k = 1}^{m - 1} [(m - k) \cdot c_{(m - k)} \cdot a_{k}]$

$P = \exp (C_{0})$

where $m = 1, 2, 。。。, p$ 。

Parameters

转换类型: ChooseLPCs to cepstral coefficients或者Cepstral coefficients to LPCsto specify the domain into which you want to convert your coefficients.
Specify P: Choosevia input portto input the values of prediction error power using input port P. Select假设P等于1to set the prediction error power equal to 1.
输出尺寸与输入大小相同: 选择此复选框时，LPC的输入向量的长度等于CCS的输出向量。
Length of output cepstral coefficients: Enter a positive scalar that is the length of each output channel of CCs.
If first input value is not 1: Select what you would like the block to do when the first coefficient of the LPC vector is not 1. You can chooseReplace it with 1,归一化,归一化and Warn，和错误。
Output P: 选择此复选框以从输出端口P输出每个通道的预测错误功率。

参考

Papamichalis, Panos E.Practical Approaches to Speech Coding.Englewood Cliffs, NJ: Prentice Hall, 1987.

万博1manbetx支持的数据类型

双精度浮点
单精度浮点

Levinson-Durbin	DSP System Toolbox
LPC to LSF/LSP Conversion	DSP System Toolbox
LSF/LSP to LPC Conversion	DSP System Toolbox
LPC to/from RC	DSP System Toolbox
LPC的/ RC自相关	DSP System Toolbox
Real Cepstrum	DSP System Toolbox
Complex Cepstrum	DSP System Toolbox

LPC to/from Cepstral Coefficients

图书馆

描述

Algorithm

LPC to CC

CC至LPC

Parameters

参考

万博1manbetx支持的数据类型

See Also

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

LPC to/from Cepstral Coefficients

图书馆

描述

Algorithm

LPC to CC

CC至LPC

Parameters

参考

万博1manbetx支持的数据类型

See Also

Extended Capabilities

C/C++ Code GenerationGenerate C and C++ code using Simulink® Coder™.

Version History

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.