n-Queens-In-Matlab

It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described

read a file and convert it to binary ,so u can modify it and see ones and zeros

基于模糊自适应pso的电力系统负荷调度算法，采用的测试案例是标准1ee6g系统，约束条件包括机组出力上限限制、网络损耗和功率平衡。(Based on fuzzy adaptive pso scheduling algorithm of power system load, the test case is a standard 1 ee6g system, constraint conditions including limit the output of generating unit, the network loss and power balance.)

Convert Analogue to Diditall

matlab语言编写写的求两个相同大小彩色图像HSV空间的巴氏距离(matlab language written request two HSV color image the same size space Bhattacharyya distance)

Optimum array processing 最优阵列处理技术 第十章 MATLAB程序 DOA MUSIC ESPRIT(Optimum array processing DOA MUSIC ESPRIT)

1. 在matlab中分析基于分离变量法的解析解； 2. 利用简单迭代法求解，与解析法结论对比，分析求解结果的精确度。分析过程至少包括：在网格尺寸为0.1 m和1 m两种条件下，两次迭代差值最大为10-10时的分析结论； 3. 利用超松弛迭代法分析，选择松弛因子，分析其对收敛速度（即迭代次数）的影响，并确定最优值。分析过程至少包括：在网格尺寸为0.1和1两种条件下，两次迭代差值最大为10-10时，迭代次数随松弛因子的变化，得到对应的最优松弛因子，与经验值（课本165页式子3.7.15）进行对比。(1. Analyze the analytical solution based on the separation variable method in matlab. 2. Using a simple iterative method to solve, compared with the results of the analytical method to analyze the accuracy of the solution. The analysis process at least includes the following conclusions: when the mesh size is 0.1m and 1m, the maximum difference between two iterations is 10-10. 3. Analyze using the relaxation relaxation iteration method, select the relaxation factor, analyze its influence on the convergence speed (ie the number of iterations), and determine the optimal value. The analysis process at least includes the following: when the mesh size is 0.1 and 1 and the maximum difference between two iterations is 10-10, the number of iterations varies with the relaxation factor, and the corresponding optimal relaxation factor and empirical value are obtained ( Textbook 165 pages (3.7.15) for comparison.)

You can see your digital clock by matlab and just simulink.

增强的AMR编码器快速固定码本搜索方法-【专利】 (fast fixed codebook search method for enhaced AMR [patent])

用Matlab程序实现P阶Levinson-Durbin算法。以一个2阶自回归模型（参数为b0=1, a1=0, a2=0.81）和一个2阶滑动平均模型（参数为b0=1, b1=1, b2=1）为例，选取观测数据长度为1000，分别用一个AR(2)模型和一个AR(10)阶模型来估计其功率谱。设激励信号模型的高斯白噪声的均值为0，方差为1。用Levinson-Durbin算法迭代计算AR模型参数，并用估计出的AR模型参数画出观测信号的功率谱。并对Levinson-Durbin算法的性能进行分析。(Write a small MATLAB program that implements the pthorder Levinson-Durbin (L-D). Run/Test the program using a AR(2) process (b0=1,a1=0, a2=0.81) and an MA(2) (bn=1,1,1) process-about 1000 samples. Use L-D with p=2 (for the AR) and 10 (for the MA). Plot the AR spectra produced in the two cases with L-D. List the direct form and the reflection coefficients in a table. Profile the L-D (total number of computations for a pthorder)