dnoising-matlab-code

acl细粒度访问控制机制 简单易懂 能够成功运行(The acl fine-grained access control mechanism Easy to understand To be able to run successfully)

线性调频脉冲压缩的Matlab程序,代码里有很完整的注释和解释，单径或多径瑞利衰落信道仿真。( LFM pulse compression of the Matlab program, Code, there are very complete notes and explanations Single path or multipath Rayleigh fading channel simulation.)

法国人的HHT程序中，计算瞬时频率和幅值的一个函数(The French HHT program to calculate the instantaneous frequency and amplitude of a function)

三角级数法求路面时域模型，并应用pwelch方法求其功率谱密度，与标准路面功率谱密度进行对比(Trigonometric series method for road surface model in time domain, and the application of the pwelch method for its power spectral density, and the standard of pavement power spectral density contrast )

matlab实现的粒子滤波器源代码，多若干实例并有与Kalman滤波器性能的比较(realize the particle filter matlab source code, and more with some examples and compare the performance of Kalman filter)

This program has evolved over time and uses programming

说明：  曲线标记改变的MATLAB程序。需要的来下载。(Curve marked change in the MATLAB program. Need to download.)

MIT--航空航天工程中的计算方法_最优化方案 MIT公开课程--航空航天工程中的计算方法 这门课程适用于在航空和航天工程中出现的计算方法的入门学习。其应用是从航空宇宙结构，空气动力学，动力学和控制，和航空宇宙系统选出的。其技术包括：常微分方程系统的数值积分；偏微分方程式的有限差分,有限体积, 和有限元的离散化；数值线性代数；本征值问题和带有约束的最优化。 (MIT- Aerospace engineering calculations _ MIT open course program optimization- Aerospace engineering calculation methods for this course in aviation and aerospace engineering calculations appear in an introduction. The application is from aerospace structures, aerodynamics, dynamics and control, and aerospace systems selected. The technologies include: numerical integration of ordinary differential equations systems partial differential equations of finite difference, finite volume, and finite element discretization numerical linear algebra eigenvalue problems with constraints and optimization.)

This is a fast non-iterative ellipse fit, and among fast non-iterative ellipse fits this is the most accurate and robust. It takes the xy-coordinates of data points, and returns the coefficients of the equation of the ellipse: ax^2 + bxy + cy^2 + dx + ey + f = 0, i.e. it returns the vector A=(a,b,c,d,e,f). To convert this vector to the geometric parameters (This is a fast non-iterative ellipse fit, and among fast non-iterative ellipse fits this is the most accurate and robust. It takes the xy-coordinates of data points, and returns the coefficients of the equation of the ellipse: ax^2+ bxy+ cy^2+ dx+ ey+ f = 0, i.e. it returns the vector A=(a,b,c,d,e,f). To convert this vector to the geometric parameters )

Huffman Coding Algo designed by one of my friends