关联维

matlab源码设计距离测算源码实例matlab source code design examples from the measurement source(matlab source code design examples from the measurement source matlab source code design examples from the measurement source)

经典的图像修复程序，matlab语言描写(The classic image fix, matlab Descriptions)

matlab code for ray leigh

biosig生物工具箱,免费哦，经测试完全可以用(biosig4octmat-2.82 include biosig,NaN,tsa biosig_installer.m )

超宽带无线通信的NAKAGAMI信道的各种经典论文。对于该信道的uwb学习很有指导作用(UWB ，NAKAGAMI channel)

说明：  如果厚度为5mm的物质对500nm光的折射率为1.4，对600nm光的折射率为1.5，画出500nm与600nm光同时照射时候观察屏上的强度分布 对牛顿环进行模拟(Newton ring analog if a thickness of 5mm substances on the refractive index of light of 500 nm is 1.4, the 600nm light refractive index of 1.5, draw 500nm and 600nm light irradiation when the intensity distribution on the viewing screen )

matlab 音频处理工具箱 音频编辑 计算频谱分析(audio processing toolbox)

matlab code for salt and pepper noise removal

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来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, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.)

基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。 (Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.)