analysis

说明：  维纳滤波器的原理及实现,有详细的推导过程(Principle and realization of the Wiener filter, a detailed derivation)

准谐振变流器matlab/simulink仿真程序，观察模型特性(quasi-resonant converter Matlab/Simulink simulation program to observe the model characteristics)

MATLAB信号处理详解、基于Simulink的OFDM通信系统仿真、基于MATLAB的系统分析与设计。(Detailed signal processing MATLAB, Simulink-based OFDM communication system simulation, MATLAB-based system analysis and design.)

粒子群优化算法是一种新的智能优化算法，用于解决最小值问题，寻求最优解。(Particle swarm optimization is a new intelligent optimization algorithm for solving the minimum problem, finding the optimal solution.)

ALOHA算法的仿真，对于算法的过程用mutlab进行了仿真(Frame slot ALOHA algorithm simulation)

The M-file generates modulated signals using BPSK, QPSK, 16QAM and 64QAM modulation.

some thing more for MIMO

1. 608组样本，第一列数字是标号，第二列数字是出现损坏的时间，第三列表示数据有效性，为0有效 2. 损坏时间是对数正态分布的，需要拟合 3. 求均值80%置信区间 4. 成本为m，价格为s，保证盈利20%，选取保修期 5. 比较保修期和拟合数据的均值 6. 若保修期就是拟合损坏时间的均值，求出利润率 loadd.m：加载样本数据，并选取有效数据 period.m：加载成本、价格数据，计算利润和保修期的关系(1.608 groups of samples, the first number is the label, the second column number is the time to appear damage, the third list shows the validity of the data, which is 0 effective. 2. damage times are logarithmic normal distribution and need to be fitted 3. mean in 80% confidence interval 4. the cost is m, the price is s, the profit is 20%, the warranty period is selected. 5. compare the mean value of the warranty period and the fitting data 6. if the warranty period is to fit the mean damage time, the profit rate is calculated. Loadd.m: load the sample data and select the valid data Period.m: loading cost, price data, and calculating the relationship between profit and warranty period)

说明：  LDPC码的比特翻转译码算法，其中包含一些可用的码字，EG-LDPC码和PEG构造的码字。(The bit flipping algorithm for LDPC codes.)

仿真对象如下： 其中， v( k )为服从N (0,1) 分布的白噪声。输入信号u ( k) 采用M 序列，幅度为 1。M 序列由 9 级移位寄存器产生，x(i)=x(i-4)⊕x(i-9)。 选择如下辨识模型： 加权阵取Λ = I。 衰减因子β = 0.98，数据长度 L = 402。 辨识结果与理论值比较，基本相同。辨识结果可信 (he simulation object is as follows: among them, v (k) to obey N (0, 1) distribution of white noise. The input signal u (k) using M sequence, amplitude is 1. M sequence by 9 level shift register generation, x (I) = x (I- 4) ⊕ x (I- 9). Choose the identification model: weighted array take Λ = I. Attenuation factor β = 0.98, the data length L = 402. Identify the theoretical calculation and comparison, basically the same. Identification results are reliable)