这种方法首先对非语言声音信号进行谐波分析，然后对所得到的时变振幅与频率等声音信号参数进行分段线性化。
This technique performs harmonic analysis of the nonspeech audio signals and then the resulted attributes including time-varying amplitude and frequency functions are piecewisely linearized.
从波动方程出发推导了各分段的位移及应变的表达式，同时给出了频率方程。
Based on wave equation, the formula of displacement and strain in different section are derived, and the frequency equation is given.
为了解决这个问题，提出了一种新的频率估计算法，采用扩频调制信息消除策略和分段相关FFT频谱分析技术实现频偏精确估计。
To solve this problem, a new method of frequency offset estimation is proposed. This method adopts modulated data elimination technique and the segmental correlation FFT algorithm.
一是利用分段FFT的相位差修正算法，二是基于二次内插的频率FF T校正法。
One method is phase difference correction of partly FFT; the other is FFT frequency correction with quadratic interpolation.
该文采用上述情形的多普勒频率的分段一阶近似模型，在此基础上，提出一种基于推广RELAX算法的线性调频信号参量估计方法。
In this paper, the first order approximate model of Doppler frequency is assumed, and an algorithm based on the extended RELAX method is proposed to estimate the parameters of chirp signals.
分别给出了分段线性化和分段变频率两种定标方法的编程思路，可提高非线性模拟量检测的精度和局部分辨率。
Two calibration method programming ideas of piecewise linear and piecewise frequency are given which can improve the accuracy of detection of non-linear mini-two and partial resolution.
电磁耦合频率效应特性曲线在双对数座标纸上具有较好的分段线性化特点。
The response curves of frequency effects of EM coupling in logarithmiccoordinates have distinctive fe…
分段电极总长度及分段电极的分段数两者需要由待测电场的频率响应带宽和灵敏度要求来综合考虑取值。
Some fabricated optical electric field sensors with segment electrode were used to test the sensitivity, the frequency response and the linearity dynamic range.
对微地震信号预分段，用小波提取其频率谱中的频率特征，得到了频率变化的四种趋势。
The signals were divided into segments and the frequency spectra were got and the frequency features were achieved and 4 types of variation of frequency were found.
对微地震信号预分段，用小波提取其频率谱中的频率特征，得到了频率变化的四种趋势。
The signals were divided into segments and the frequency spectra were got and the frequency features were achieved and 4 types of variation of frequency were found.
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