suduGame

说明：  此代码可以用于实现地理加权回归分析；包括普通的地理加权回归和贝叶斯地理加权回归；包含算法代码和应用实例的代码(Geographically weighted regression analysis)

说明：  克里金(Kriging)插值法又称空间自协方差最佳插值法，它是以南非矿业工程师D．G．Krige的名字命名的一种最优内插法。克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。(Kriging interpolation, also known as spatial autocorrelation optimal interpolation, is named after d.g.krige, a mining engineer in South Africa. Kriging method is widely used in groundwater simulation, soil mapping and other fields. It is a very useful geostatistical grid method. Firstly, it considers the variation distribution of spatial attributes in spatial position, determines the range of distance that affects the value of a point to be inserted, and then estimates the attribute value of the point to be inserted with the sampling points in this range. This method can provide the best linear unbiased estimation (the determined value at a certain point) for the studied object mathematically.)

经典，且少有的基于Win32汇编语言开发内核模式驱动程序的教程，作者为俄罗斯的大牛(Classic, and rare in assembly language based on the Win32 kernel mode driver development tutorial, the writer for Russia s large cattle)

基于dsp28377的pwm波产生的完整工程文件(Complete engineering document produced by PWM wave based on dsp28377)

DPD算法，包括波动方向信息和时延信息，可正常运行随意扩展(Direct Position determination algorithm)

自己遍的牛顿迭代法求解二元二次方程的程序 迭代步数可以自己设定-Their times of Newton iteration procedure for solving the dual quadratic equation iteration step can be set for

正弦信号的频率，相位，幅度等参数的最小二乘法拟合(sine signal parameters fitting)

说明：  Dobson模型作为一个函数，输入参数为：频率，温度，体积含水量，砂粒含量，粘粒含量，容重。 每个参数都只能是标量，不能是矩阵。 输入说明： 频率：单位是GHz 温度：单位是℃ 体积含水量：单位是cm3/cm3，范围是0~1 砂粒含量，粘粒含量：范围是0~100(Dobson model as a function, the input parameters are: frequency, temperature, volume water content, sand content, clay content, bulk density. Each parameter can only be scalar, not matrix.)

锅炉汽包水位自适应模糊控制 仿真可以很好运行(Boiler bubble water control can realize the simulation of boiler water level, and the effect is obvious. (control))

粒子群算法，也称粒子群优化算法或鸟群觅食算法（Particle Swarm Optimization），缩写为 PSO， 是由J. Kennedy和R. C. Eberhart等开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法(Particle Swarm Optimization (PSO), also known as Particle Swarm Optimization (PSO), is a new evolutionary algorithm developed by J. Kennedy and R. C. Eberhart. PSO is a kind of evolutionary algorithm, which is similar to simulated annealing algorithm. It starts from random solution and searches for the best solution by iteration. It also evaluates the quality of solution by fitness. But it is simpler than genetic algorithm rules. It has no Crossover and Mutation operation of genetic algorithm. As a result, it searches for global optimum by following the optimal value currently searched. This algorithm has attracted the attention of academia for its advantages of easy implementation, high accuracy and fast convergence, and has shown its superiority in solving practical problems. Particle swarm optimization is a parallel algorithm)