ChaosAttractors

Quadratic Assignment Problem BPSK

大量实验表明,提出的方法对同种传感器或者不同传感器图像之间的配准都是有效的。 提出了一种新的基于角点检测的图像配准方法,其核心思想是采用一种快速的 基于图像灰度的角点检测新算法,通过沿圆弧曲线扫描获取角点信息,然后根据这些 角点信息建立图像间角点的对应关系,并由此得到初配准参数,最后通过迭代过程以 提高配准的精度. 理论分析和实验结果表明,该算法对图像间的旋转角度没有限制, 配准精度高而且计算量较小. (Experiments show that the proposed method on the same kind of sensor or between the different sensor image registration is valid. A new corner detection based image registration method, the core idea is to use a fast gray-based new algorithm for corner detection, scanning through the curve along the arc for corner information, and then based on these corner information to establish image correspondence between the corners, and thus be the beginning of registration parameters, and finally through the iterative process to improve the accuracy of registration. Theoretical analysis and experimental results show that the algorithm is rotation between the image does not limit , registration accuracy and less computation.)

无监督神经网络利用matlab能够有效的实现图像化，还能得到最有结果(Unsupervised neural network using matlab can effectively realize the image of, but also get the most results)

该算法是以粒子群中粒子的收敛特性为基础,依据量子物理理论提出的,改变了传统粒子群算法的搜索策略,可使粒子在整个可行解空间中搜索寻求全局最优解。同时该算法的进化方程中不需要速度向量,而且进化方程的形式更简单,参数较少且容易控制。对两个算例进行仿真测试,证实该算法可有效解决经济负荷分配问题 性能对比显示,该算法求得的解优于已有的改进粒子群算法及其它优化算法所求得的解。(The algorithm is based on convergence particle swarm particle basis, according to the theory of quantum physics, particle swarm algorithm has changed the traditional search strategies, allow the particles throughout the feasible solution space search seek the global optimal solution. Meanwhile, the algorithm does not need velocity vector evolution equations, and evolution equations simpler and less parameters and easy to control. Two examples of simulation tests confirmed that the algorithm can effectively solve the economic load allocation performance comparison shows that the algorithm is superior to existing solutions obtained improved PSO algorithm and other optimization algorithms obtained solution.)

说明：  matlab图像处理基础源码 1、jpeg压缩 2、6个基本图像压缩源码 3、小波源码(Matlab based image processing a source, jpeg compression 2,6 basic image compression source 3, wavelet FOSS)

随机信号仿真数据的生成的matlab程序(Random-signal simulation data generated by matlab program )

BFSK信号经高斯白噪声信道仿真Simulink仿真(BFSK signals by Gaussian channel simulation)

EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions):Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Semicircle, Yule, Zeta,(EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions): Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Sem)

关于神经网络算法在MATLAB中对典型二阶对象进行仿真，并得到其阶跃响应。。(MATLAB)

PD control for robotics with disturbance