sin

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)

梁元进行有限元分析时可利用的函数，很不错，有一定价值(Beam element for finite element analysis of available functions, very good, there is some value)

MATLAB中实现PID控制系统的，改变输入r(k）分别为阶跃信号、三角波、方波。(MATLAB to achieve PID control system, change the input r (k) are step signal, triangle wave, square wave.)

遗传算法matlab的工具箱，关于遗传算法的matlab基本编程程序(Genetic algorithm matlab toolbox genetic algorithm matlab basic programming procedures)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

simulink的仿真有两个阶段：一个为初始化，这个阶段主要是设置一些参数，像系统的输入输出个数、状态初值、采样时间等；第二个阶段就是运行阶段，这个 阶段里要进行计算输出、更新离散状态、计算连续状态等等，这个阶段需要反复运行，直至结束。(simulink simulation has two phases: one for initialization, this stage is mainly to set some parameters, such as the number of input and output system, initial state, the sampling time second stage is the operational phase, the Stages to calculate the output, update the discrete state, continuous calculation of the state, etc., this stage requires repeated runs to the end.)

selection diversity MATLAB code

NC-OFDM在六径瑞利衰落信道下的性能分析(NC-OFDM in the six path Rayleigh fading channel performance analysis)

matlab经典课件2(matlab courseware classic 2)

实现对数压缩PCM和线性PCM的信噪比特性曲线的仿真，非均匀量化级数为n=8和n=6。(realization of a number of PCM compressed and linear PCM signal-to-noise ratio of the characteristic curve simulation, non-uniform quantization Series n = 8 and n = 6.)