F_computation_v1

此源码程序是自适应滤波中的应用LMS算法进行仿真。对LMS算法的性能 收敛速度进行了研究(The source process is the application of adaptive filtering LMS algorithm simulation. The performance of the LMS algorithm convergence rate have been studied)

Matlab中所有的函数，用户可以方便地使用(Matlab, all functions, users can easily use)

there are some newly released Neural Network Example Programs for Character Recognition, which based on Image Processing Toolbox,Neural Network Toolbox in MATLAB, which is quite informative for the beginners in Neural networks applicators(there are some newly released Neural Network Example Programs for Character Recognition, which based on Image Processing Toolbox, Neural Network Toolbox in MATLAB, which is quite informative for the beginners in Neural networks applicators)

The document is offered to support C5300 module application and development, which is provided to LONGSUNG’s customers for testing, uation, integration and information purposes.

PARAFAC 用于多维数据分辨与校正(PARAFAC For multidimensional data resolution and correction)

这是关于二自由度直升机模型的前向控制和反馈控制的simulink仿真模型(This is the simulink simulation model helicopter model before about two degrees of freedom to control and feedback control)

说明：  实现多尺度熵的算法 多尺度熵（Multiscale entropy, MSE）将样本熵扩展到多个时间尺度，以便在时间尺度不确定时提供额外的观察视角。样本熵的问题在于它没有很好地考虑到时间序列中可能存在的不同时间尺度。为了计算不同时间尺度下信号的复杂性，Costa等人（2002,2005）提出了多尺度熵。(MultiScale Entropy There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.)

spatial multiplexing in MIMo matlab code

这是中心近邻分类器的算法，采用的算子是LBP，数据库采用的是CK数据库。(This is the center of neighbor classifier algorithm, is the LBP operator is used, the database USES a CK database. )

MATLab speech recognition soft