Function-quick-manual-of-MATLAB

This a one dimensional level set code where the interface grows with normal speed equal to one. The code generates a movie showing the interface motion and the evolution of the level set function.

try classification of ecg signal

艾特肯插值方法源代码，用于科学计算和数据插值，适合学习matlab及工程技术人员参考。(Aitken interpolation source code for scientific computing and data interpolation, for learning matlab and engineering and technical officers.)

Approximate Greedy Solutions to the problem min||x(k)||_2,0 such that Ax = b

用局部参数最优化方法设计一个模型参考自适应系统,可调增益的初值Kc(0)=0.2，给定值r(t)为单位阶跃信号，即r(t)=A×1(t)。 要求： 1把连续系统离散化(采样时间可取0.1)。 2编制并运行这个系统的计算机程序(注意调整B值，使系统获得较好的自适应特性)。 3记录ym、yp的曲线 记录kp×kc的曲线 记录广义输出误差e的变化曲线。 4在参数收敛后，让Kp=2变为Kp=1，重新观察Kp×Kc及e的变化曲线。 5找出在确定的B值下，使系统不稳定的A值(阶跃信号的幅值)，并与用劳斯稳定判据计算的结果比较。 (With local parameter optimization method to design a model reference adaptive system, adjustable gain initial Kc (0) = 0.2, for a given value of r (t) for the unit step signal that r (t) = A × 1 ( t). Requirements: a continuous system discretization (sampling time of 0.1 preferred). 2 compiled and run the system computer program (Note B to adjust the value of the system to obtain better adaptive characteristics). 3 records ym, yp curve record kp × kc curve records generalized output error e curves. 4 parameter convergence, let Kp = 2 into the Kp = 1, re-observed Kp × Kc and e curves. B-5 to find value in determining the next, making the system unstable A value (step signal of amplitude), and using Routh stability criterion and the comparison of the results calculated.)

Spectral Analysis using the FFT

语音提取和分析，运用LPC的方法对语音信号进行分析以及最终的合成。(Voice extraction and analysis using a method of LPC analysis of the voice signal as well as the final synthesis.)

说明：  使用遗传算法优化36单元圆形天线阵列,有需要的可以分享一下(optimise the 36 elements of antena arrays)

生成BA无标度网络，并统计网络的度分布（网络中新家入的节点会优先选择网络节点度较大的节点链接）。(The BA scale-free network is generated and the degree distribution of the network is counted (the new home nodes in the network will preferentially choose the node links with higher degree of network nodes).)

核主成分分析方法，是主成分分析的一种改进算法，是一种非线性的特征提取方法。 (Kernel principal component analysis, is the principal component analysis of an improved algorithm, is a nonlinear feature extraction method.)