搜索资源列表
gongzhen
- 描述阀值系统中的随机共振现象，其中fazhi2是二进制随机信号加入高斯噪声的随机共振现象。-System descr iption of threshold stochastic resonance phenomenon, which is a binary random signal fazhi2 adding Gaussian noise of the stochastic resonance phenomenon.
lpctoolbox_v20
- 本工具箱利用lpc方法可以准确的提取出共振峰频率，并且解决了共振峰检测时滤波器阶数对所有说话人都一样的问题。本工具箱由美国卡内基梅隆大学一位教授编写，因此所有解释均为英文原版。-The toolbox to use LPC method can extract accurate formant frequency, and the resolution of formant filter order testing of all the speaker are the same problems
coleawin_Matlab_Speech_Analysis
- 波形和频谱双显示 记录讲话直接进入MATLAB 手动分割讲话波形-创建标签文件 波形编辑-切割，复制或粘贴 共振峰分析-显示共振轨道的F1 ， F2和F3 基音分析 过滤工具-语音信号滤波器截止频率 比较工具-比较两个波形的频谱距离使用几种措施 增加噪声-Dual time-waveform and spectrogram displays Records speech directly into MATLAB NEW Displays time-a
gongzhenok
- 产生随机共振现象的输入输出信噪比曲线，参数可以修改，不过不要乱改动哦，不然振动不起来了。-Stochastic resonance phenomenon generated input and output signal to noise ratio curve.
SNR
- 随机共振相似度的Matlab计算程序，计算看出输入-输出的相似度S随着噪音的标准差的增大而不断得到改善，直到增大至一饱和值为止-an example for SR
formant
- 利用matlab软件提取共振峰参数 -Formant extraction can be used for voice recognition technology
my_lpc
- 线性预测（LPC）是语音信号处理中最有效的分析方法之一，通过LPC谱，LPCC谱的分析，并结合LPC检测方法判断出语音的基音周期或共振峰。我们可以利用Matlab来进行编程实现，具有实现简单，效果良好的特点-The linear predictive (LPC) is one of the most important methods in speech processing. Through the LPC spectrum, the LPCC spectrum analysis, and u
F0F1F2F3
- 语音信号使用lpc线性预测法识别并提取共振峰，共振峰提取技术是语音识别和语音合成的关键。-Using lpc line estimate method identifies and withdraws the resonance in speech signal, the technique of resonance withdraws is the key of the speech understanding and speech synthesis.
srchengxu
- 随机共振的相关程序，资源齐全.货真价实。希望能对大多数研究随机共振的人有一定的帮助-it is very goood
haodongxi
- 随机共振的很多例子的集合体。matlab代码可以作为参考。-Stochastic resonance in a collection of many examples. matlab code as a reference.
5956457lpc
- 语音信号的线性预测编码分析，生成语音信号的波形图，共振峰-The linear predictive coding speech signal analysis, speech signal waveform is generated, formant
pitchdetection
- 自相关法基音检测的MATLAB代码。自相关法计算速度较快的自相关函数法检测语音的基音频率，有效剔除了高频共振峰和噪音的影响，其估计基音频率准确性高，稳定性好，运算速度较快。-CAMDF
NSR
- 随机共振的弱信号检测，运用朗格万方程进行MATLAB的仿真-stochasitc resouance using for detecting the weaken signals,based on longawan function
SR
- 通过双阈值系统中的随机共振特性，研究含有高斯白噪声的信号。-is investigated the characteristics of stochastic resonance of the signal added Gaussian white noise in a bithreshold system
sr
- 双稳态随机共振与时间同步的相关性研究可以改变随机共振原则改变系统工作环境-is investigated the characteristics of stochastic resonance of the signal added Gaussian white noise in a bithreshold system
audio
- 调制与解调用于随机共振的微弱周期信号检测DSP实现-DSP C
lpctrack.m
- 采用线性预测的方法来实现语音信号的共振峰估计。-Speech formant estimation by LPC Method
sr
- 微弱信号检测的随机共振方法与应用研究 博士生论文-Stochastic resonance in weak signal detection method and application of doctoral thesis
F0F1F2F3
- 本算法是通过共振峰的方法，利用信号的倒谱特性对语音信号进行处理。-This algorithm is the method by the resonance peak, the signal characteristics of the cepstrum of the speech signal processing.
89346499sr
- 产生随机共振现象的输入输出信噪比曲线,运用龙格库塔算法求解朗之万方程，进而实现随机共振系统-the realization of stochastic resonance systems