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wave_neural_crossvalind
- 应用连续小波变换对脑机接口（BCI）信号处理，进入神经网络分类，包括BP网络和LVQ网络-continuous wavelet transform application of brain-machine interfaces (BCI) signal processing, neural network access classification, BP network including network and LVQ
modulate_identify
- 基于小波变换的调制识别方法.里面包含如下内容：QAM、PSK、FSK、AM和OFDM信号源生成程序，基于小波变换的QAM、PSK和FSK信号分类算法的程序，利用小波变换区分OFDM信号与数字单载波信号的算法程序，利用OFDM信号自相关特性分类OFDM信号与模拟信号的算法的程序。
Wavelet-transform
- 原始信号是含有奇异点的信号，为确定该奇异点的时间，采用haar小波进行连续小波变换后，在对系数进行分析处理。-The original signal is containing singular point of the signal, in order to determine the singular point time, adopting haar wavelet to continuous wavelet transform, the coefficients in analyzed
对白噪音信号进行基于小波变换尺度为n的分解
- 对白噪音信号进行基于小波变换尺度为n的分解
fuzzy
- 一份介绍小波变换的论文，包括突变点的检测以及信号降噪等。-Introduce a wavelet transform of papers, including the detection of point mutations, as well as signals such as noise reduction.
WaveletClassLib
- 一个多维离散小波变换类代码。这个类可以分析的多维输入信号和处理后合成它。输入信号可以是一维信号（例如一个波），二维信号（如图像）或多维信号。 - a class of multidimensional discrete wavelet transform. This class can analyze the multidimensional input signal and synthesize it after process. The input signal can be
1HIBERT
- hilbert提取心音包络.此程序包含心音信号的低通滤波、小波去噪、EMD分解、希尔伯特黄变换以及心音阈值定位一系列算法。-hilbert extract PCG envelope low pass filter This program contains heart sound signals, wavelet de-noising, EMD decomposition, Hilbert-Huang transform and heart sound threshold locate a se
ewt
- 经验小波变换，一种新的自适应信号处理方法-Empirical wavelet transform, a new adaptive signal processing method
us846
- 分数阶傅里叶变换计算方面,基于小波变换的数字水印算法matlab代码，小波包分析提取振动信号中的特征频率。- Fractional Fourier transform computing, Based on wavelet transform digital watermarking algorithm matlab code, Wavelet packet analysis to extract vibration signal characteristic frequency.
IUQCWY
- 小波变换在语音和生物医学信号处理中的应用 小波变,-Wavelet transform in speech and biomedical signal processing, the application of wavelet change,
speech__traksform
- 小波变换在语音和生物医学信号处理中的应用 小波变,-Wavelet transform in speech and biomedical signal processing, the application of wavelet change,
wind power forecasting based on EWT-KELM
- 针对短期风电功率预测，提出一种基于经验小波变换预处理的核极限学习机组合预测方法。首先采用 EWT 对风电场实测风速数据进行自适应分解并提取具有傅立叶紧支撑的模态信号分量，针对每个分量分别构建 KELM 预测模型，最后对各个预测模型的输出进行叠加得到风速预测值并根据风电场风功特性曲线可得对应风电功率预测值。(Aiming at short-term wind power prediction, a kernel-based learning machine combination predicti