han_eso

无线通信高斯白噪声信道各类调制方式，并且有星座图、调制曲线分析。(Wireless communications Gaussian white noise channel types of modulation methods, and has constellation, modulation curve analysis.)

说明：  de Boor 求值算法求作二次和三次B-样条曲线非插值，给定顶点(algorithm evaluates demand for secondary and cubic B-spline- curve interpolation, given vertex)

说明：  基于遗传算法的OFDM自适应资源分配算法MATLAB源码 OFDM自适应资源分配问题（载波、功率等），是一个既含有离散决策变量，又含有连续决策变量的非线性优化模型，且含有较为复杂的非线性约束，因此适合采用智能优化算法进行求解。 (Adaptive genetic algorithm-based resource allocation algorithm for OFDM OFDM MATLAB source adaptive resource allocation problem (carrier, power, etc.), is a decision with both a discrete variable, but also with continuous decision variables of the nonlinear optimization model, and contains more complex non-linear constraints, so smart optimization algorithm for solving.)

此程序是关于阵列信号处理中的最佳波束扫描，程序简单易懂，便于我们理解理论知识。(The program is about array signal processing the best of the beam scanning, and the program is easy, and for us to understand the theory of knowledge. )

这是 Andrew Ng 机器学习讲义《Reinforcement Learning and Control》,包含了离散和连续MDP的内容，比官网的课件全。（官网的缺乏连续MDP部分）(This is Andrew Ng Machine Learning Materials " Reinforcement Learning and Control" , contains a discrete and continuous MDP content than the official website of the courseware whole. (Official website of the lack of continuous MDP section))

sinX函数，一个输入对应一个输出，最后在matlab上显示sin函数图形(SinX function, an input corresponding to an output, the sine function is displayed in the matlab graphics )

自举是一种由重采样估计，独立和（蒙特卡洛重采样）等概率设置一个单一的数据统计变化的一个途径。允许的措施估计那里的潜在分布是未知的或者样本量很小。他们的结果与这些分析方法的统计特性相一致。 在这里，我们使用非参数逼近。非参数引导更简单。它不使用该模型的结构，建造人工数据。矢量[易西]是重采样，而不是直接与replecement。这些参数是从这些对构建。 二，回归模型时，应使用在回归方程中的两个变量是随机的，会有错误的，即不是由研究者控制。模式，我用普通最小二乘回归低估了变量之间的错误时，他们都含有线性关系的斜率。据索卡尔和罗尔夫（1995），模型二回归的主题是一对哪些研究和争论仍在继续，最终建议是很难做出。 BOOTGMREGRESS模型II是一个引导程序。这需要s引导和规范样品前坡计算变量。这两个变量的每个转化为具有零均值和标准差的一个。由此产生的斜率是线性回归系数的Y在X里克创造了这个词（1973）几何平均数并给出了一个模型II回归广泛审查。它也被称为引导标准的主要轴线(The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their results are consistent with the statistical properties of those analytical methods. Here, we use the Non-parametric Bootstrap. Non-parametric bootstrap is simpler. It does not use the structure of the model to construct artificial data. The vector [yi, xi] is instead directly resampled with replecement. The parameters are constructed from these pairs. Model II regression should be used when the two variables in the regression equation are random and subject to error, i.e. not controlled by the researcher. Model I regression using ordinary least squares underestimates the slope of the linear relationship between the variables when they both contain error. According to Sokal and Rohlf (1995), t)

MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). This book provides a comprehensive introduction to the basic theory and practice of wireless channel modeling, OFDM, and MIMO, with MATLAB
programs to simulate the underlying techniques on MIMO-OFDM systems. This book is primarily designed for engineers and researchers who are interested in learning various MIMO-OFDM techniques and applying them to wireless communications. It can also be used as a textbook for graduate courses or senior-level undergraduate courses on advanced digital communications. The readers are assumed to have a basic knowledge on digital communications, digital signal processing, communication theory, signals and systems, as well as probability and random processes.

说明：  matlab-pid controller

QPSK transmitter in matlab