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说明：  Matlab源代码，EM Algorithm(EM Algorithm)

C/C++ and Matlab types convertor

Modeling crack growth in a traditional finite element framework is a challenging engineering task. Originally the finite element framework was modified to accommodate the discontinuities that are caused by phenomena such as cracks, inclusions and voids. The finite element framework is not well suited for modeling crack growth because the domain of interest is defined by the mesh. At each increment of crack growth, at least the domain surrounding the crack tip must be remeshed such that the updated crack geometry is accurately represented.

说明：  本文研究了GPS接收机的捕获算法，并基于Matlab软件平台和射频前端在Pc上实现了GPS软件接收机样机。(In this paper, the GPS receiver to capture algorithms, and Matlab-based software platform and the RF front-end has been realized in the Pc software GPS receiver prototype.)

说明：  多载波调制，信道优化后的dmt程序，图像显示调整结果(Multi-carrier modulation, channel optimized dmt procedures, image display adjustment)

说明：  matlab教程 提供详细的技术说明，并附上源代码(matlab tutorials provide detailed technical description, together with the source code)

等间距线性阵列，阵元数M=8，阵元间距d= λ /2，等幅加权，目标方位φr =0°。产生空间白噪声矢量（复高斯分布）。 设阵列信号矢量元素s(m)=exp[j mψr]，其信号幅度为1，该阵元接收机附加的高斯噪声为n(m)=nmr+jnmi，其中实虚部均为独立同分布N(0, σ2)的高斯随机数，则该通道合成信号x(m)=s(m) + n(m)，其中信噪比为： SNR = 10 lg[1/(2σ2)] = – 3 – 10 lg(σ2) (dB) (The spacing of the linear array, and the array element number M = 8, the array element spacing d = λ/2, equal amplitude weighted target azimuth φR = 0. Space generated white noise vector (complex Gaussian distribution). Let array signal vector elements s (m) = exp [j mψr], the signal amplitude, the element receiver additional Gaussian noise n (m) = nmr+jnmi which the real and imaginary parts are independent and identically distributed N ( Gaussian random numbers of 0, σ2), the channel the synthesis signal x (m) = s (m) the PPLS n (m), where SNR is: SNR = 10 lg [1/(2σ2)] =- 3- 10 lg (σ2) (dB))

第五章的递推的极大似然法辨识程序,《系统辨识及其MATLAB仿真》附带的光盘(Chapter V of the recursive maximum likelihood identification procedure, " System Identification and MATLAB simulation" with CD-ROM)

Identification of Cardiac Arrhythmias using Natural Resonance Complex Frequencies

The goal of SPID is to provide the user with tools capable to simulate, preprocess, process and classify in vivo and ex vivo MRS signals. These tools are embedded in a matlab graphical user interface (GUI). (Pre)processing and classification methods can also be automatically run in a row using the matlab command line