nn

％ y=filter(sig,fmin,fmax) ％ 对信号进行理想滤波，可完成低通，带通 ％ sig为被滤波信号 ％ fmin为下限频率，当fmin为0时为低通滤波器，当fmin>0时，为带通滤波器 ％ fmax为上限频率，fmax>fmin ％ fs为信号的采样频率 ％ y为经过滤波后的信号 (％ Y = filter (sig, fmin, fmax)％ of the ideal signal filtering, to be completed by low-pass, band-pass filter％ sig for signal％ fmin is the minimum frequency, when fmin for 0:00 for the low-pass filter, when fmin > 0, for the bandpass filter％ fmax is the upper limit frequency, fmax> fmin％ fs for signal sampling frequency％ y for the filtered signal)

面阵中二维角度估计 UNITARY -ESPRIT算法MATLAB程序(Two-dimensional planar array angle estimation UNITARY-ESPRIT algorithm based on MATLAB program)

shape from shading with source code of matlab

ibm cics中间使用件问题解答，内部文档(ibm cics questions between the use of pieces, internal documents)

认知无线电BPSK信号的循环平稳检测的性能仿真 包含信号循环谱图(Cognitive radio spectrum cyclostationary detection performance cycle)

LDPC MATLAB 仿真源程序，希望对您有用(LDPC MATLAB simulation source, hope useful for you)

利用 Poisson 方程求解热平衡下 PN结的电势分布 (Poisson matlab PN)

图像复原 退化模型 连续退化模型 离散退化模型 复原的代数方法 代数复原原理 逆滤波复原 最小二乘方滤波 MATLAB 实现图像复原 维纳滤波复原 规则化滤波复原 Lucy-Richardson 复原 盲去卷积复原 图像复原的其它 MATLAB 函数 (Degradation of image restoration model continuous degradation model discrete degradation model recovery principles of algebra algebraic inverse filter to recover to recover MATLAB least squares filtering for image restoration Wiener filter to recover the rules-based filtering to recover Lucy-Richardson deconvolution to recover Blind Image Restoration to recover the other MATLAB Functions)

绘制人脸，通过几个圆组合出人脸、人眼等部位，然后构造动画(Draw a face to face, the human eye and other parts by several round combination, and then construct the animation)

说明：  这是一个快速的三维图像双边滤波的实现。这个过滤器平滑图像的同时保留边缘，但在其最直接的实现是非常计算的要求，特别是对大型3D图像。快速双边滤波是一种近似技术，极大地提高了计算速度。我的实现严格遵循Matlab版的快速二维滤波器，只是做了一些修改(This is an implementation of fast bilateral filtering for 3D images. This filter smoothes the image while preserving edges, but in its most straightforward implementation is very computationally demanding, especially with large 3D images. Fast bilateral filtering is an approximation technique which drastically improves the speed of computation. My implementation closely follows the Matlab version of the fast 2D filter with some modifications)