KFCM

这个matlab程序实现了牛顿插值 （Newton s Interpolation ）算法。(The matlab program implements Newton interpolation (Newton' s Interpolation) algorithm.)

改进了BIHT l2 中的观测矩阵，实验结果证明，误差更小了(change BIHT l2 ，perform better)

功率谱估计是利用有限长的数据估计信号的功率谱，广泛应用于各个领域。功率谱估计主要分为经典谱估计与现代谱估计。常用的经典谱估计方法有周期图法，相关法，周期图的改进法，常用的现代谱估计方法有最大熵谱估计，AR模型，MA模型，ARMA模型。经典谱估计适用于长序列的信号，其主要缺陷是描述功率谱波动的数字特征方差性能差，频率分辨率低，现代谱估计适用于短序列的信号，旨在改善谱估计的分辨率，并将其应用于实际地震资料的谱分析。 (Power spectrum estimation is the use of a finite length data to estimate the power spectrum of the signal, widely used in various fields. Power spectrum estimation is divided into classic and modern spectral estimation spectral estimation. Commonly used methods of classical periodogram spectrum estimation method, the relevant law, the cycle graph Improvement Act, commonly used in modern spectral estimation methods have maximum entropy spectral estimation, AR model, MA model, ARMA model. Classical spectral estimation applied to signal a long sequence, its main drawback is the fluctuation power spectrum describing digital signature variance performance is poor, the frequency resolution is low, modern spectral estimation applied to signal short sequences designed to improve spectral estimation resolution, and The analysis applied to real seismic data spectrum.)

filter based segmentation1

数字滤波器是一种用来过滤时间离散信号的数字系统，通过对抽样数据进行数学处理来达到频域滤波的目的。(FIR Digital Filter Design)

在控制工程中的应用，自动化的学生应该用的到(matlab in control engineering)

Elnagar, G., et al. (1995). "The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40(10). 上述文章的算例2的仿真代码(Elnagar, G., et al. (1995). " The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40 (10). the simulation code of example 2 in the preceding article.)

the is cuK converter designed in matlab by me.. it is closed loop operated one.. which cam regulated line as well as load

水下通信环境下，4FSK调制解调代码及bin文件,(4FSK modem code and the bin file)

matlab学习案例，有导师学习神经网络的回归拟合(the matlab case study tutor learning neural network regression fit)