搜索资源列表
Matlab
- 选择三个不同频段的信号对其进行频谱分析，根据信号的频谱特征设计三个不同的数字滤波器，将三路信号合成一路信号，分析合成信号的时域和频域特点，然后将合成信号分别通过设计好的三个数字滤波器，分离出原来的三路信号，分析得到的三路信号的时域波形和频谱，与原始信号进行比较，说明频分复用的特点。-Choice of three different signal-band spectral analysis carried out, according to the characteristics of the
mfcc
- 语音信号的初始化及MFCC特征提取算法，附带测试用语音信号-Voice signal and the initialization MFCC feature extraction algorithm, with test speech signal
music
- 输入为两个信号，采用music算法进行特征分解，实现测向的目的-Input into two signals characteristic decomposition algorithm using music to achieve the purpose of finding
BP1
- BP神经网络 数据分类 语音特征信号分类-BP neural network classification of data signal classification speech features
xsj
- 基于小波变换的碰磨故障信号的特征提取，可以画出信号原图，轴心轨迹，频谱图以及多层小波变换的重构信号-Based on wavelet transform rubbing fault signal feature extraction, the signal can be drawn artwork, orbit, spectrum and signal reconstruction wavelet multi-
Assignment2
- 国外高校老师编写的语音信号特征提取程序，非常实用初学者研究- [E, V, A, P] = analysis(x, N, U, M) extracts vocoder parameters E, V, A, and P from the speech signal x on a frame by frame basis. N is the analysis frame length, U is the update length, and M is the order of the
matlab
- BP神经网络的数据分类———语音特征信号分类 本案例选取了民歌、古筝、摇滚和流行四类不同音乐,用BP神经网络实现对这四类音乐 的有效分类。-Data speech characteristic signal classification of BP neural network, selects the guzheng, folk, rock and pop four different types of music, the realization of the four types
chapter1
- BP神经网络的数据分类——语音特征信号分类(Data classification of BP neural networks -- Classification of speech characteristic signals)
chapter1
- BP神经网络的数据分类——语音特征信号分类(Data classification of BP neural networks -- Classification of speech characteristic signals)
声音解析matlab
- 对非平稳信号进行分段、截取，再做短时傅里叶变换，分析其频谱特性，并找到各个时间节点的频率特性，以便分析不同事件段内的声音特征。(The non-stationary signals are segmented and intercepted, and then the short-time Fourier transform is used to analyze their frequency spectrum characteristics, and the frequency charact
代码
- MATLAB 代码 第1章 BP神经网络的数据分类——语音特征信号分类 第2章 BP神经网络的非线性系统建模——非线性函数拟合 第3章 遗传算法优化BP神经网络——非线性函数拟合 第4章 神经网络遗传算法函数极值寻优——非线性函数极值寻优 第5章 基于BP_Adaboost的强分类器设计——公司财务预警建模 第6章 PID神经元网络解耦控制算法——多变量系统控制 第7章 RBF网络的回归--非线性函数回归的实现 ....等58章(MATLAB code The first
chapter1
- BP神经网络的数据分类——语音特征信号分类(Data Classification of BP Neural Network - Classification of Speech Characteristic Signals)
语音短时能量、平均幅度、平均过零率
- 语音信号MATLAB特征获取，包括语音短时能量、平均幅度、平均过零率(Speech signal MATLAB feature acquisition, including voice short-term energy, average amplitude, average zero crossing rate)
aubt
- 用于分析多种生理信号，包括特征提取、特征选择和分类识别(It is used to analyze various physiological signals, including feature extraction, feature selection and classification recognition)
案例1 BP神经网络的数据分类-语音特征信号分类
- 前馈循环神经网络，用于处理语音识别,里面是matlab源代码，以及实例。学习神经网络算法很有帮助。(Feed forward recurrent neural network for speech recognition, which is the matlab source code, and an example. Learning neural network algorithms is very helpful.)
信号盒维数和稀疏性的提取_matlab
- 信号复杂度特征的提取，主要实现盒维数和稀疏性的matlab代码实现(Extracting the feature of signal complexity and realizing the matlab code of box dimension and sparsity)
R
- 自适应提取心电信号R波,经验分解加阈值法(Adaptive extraction of R waves from ECG signals)
思维进化算法优化BP神经网络——非线性函数拟合
- BP神经网络的数据分类——语音特征信号分类，matlab(Data classification of BP neural network -- speech feature signal classification)
齿轮箱信号分析
- 故障特征提取matlab程序。用于齿轮箱特征提取(Fault feature extraction matlab program.)
模拟ECG心电信号数据（matlab）
- 可以通过matlab对心电信号进行模拟，分别计算特征波并整合(ECG signals can be simulated by MATLAB, and the characteristic waves can be calculated and integrated.)