MATLAB

关于扩展卡尔曼滤波的MATLAB程序 其目标是跟踪移动物体进行定位(Multi-sensor optimal information fusion Kalman filters with applications)

Code for conversion of an image from RGB to l, alpha, beta color space and vice versa.

多样化的特点，直观和清晰的启动电压和电流的特性的过程中一个电机仿真过程的详细描述(Variety of features, intuitive and clear starting voltage and current characteristics of the process of a detailed description of the process of motor simulation)

英文书Beginning Mac OS X Snow Leopard Programming的源码。(Source code of book "Beginning Mac OS X Snow Leopard Programming")

判别稀疏非负矩阵分解，提出这个新算法，来进行人脸识别，比传统的NMF和一些其他的扩展算法效果好(Sparse non-negative matrix factorization judge proposed the new algorithm for face recognition, than the traditional extension of NMF algorithm and some other good results)

说明：  好东西 ，是关于离散卡尔曼滤波的。大家看了就知道了(good stuff is on the discrete Kalman filter. We read on to know the)

％ 该Matlab程序基于牛顿－拉夫逊算法，用于计算已知导纳矩阵、PQ节点、PV节点、平衡节点(UA)的电力网络潮流 ％ U - 各节点母线电压 S - 各节点注入功率 S_net - 电力网络总损耗 ％ PQ_P - 实算PQ节点注入有功功率 PQ_Q - 实算PQ节点注入无功功率 ％ delt_PQ_P - 实算PQ节点有功功率修正值 delt_PQ_Q －实算PQ节点无功功率修正值 ％ delt_UA_P - 实平衡节点有功功率修正值 delt_U_2 - 实平衡节点电压平方修正值 ％ delt_PQV - 实算P Q U^2修正值 J - 雅可比矩阵 ％ e - 电压实部 f - 电压虚部 delt_ef - 电压实部与虚部修正值( The Matlab program based on the Newton- Raphson algorithm is used to calculate the admittance matrix is known, PQ node, PV node, the node balance (UA) the trend of the electricity networks U- the node bus voltage S- each node injection power S_net-- The total loss of electric power networks PQ_P- operator PQ is injected into active nodes PQ_Q- operator PQ is injected reactive power node delt_PQ_P- is considered the correct value of active power PQ node delt_PQ_Q- really count PQ node reactive power to amend the value of delt_UA_P- real active power balance of the correct value of the node delt_U_2- node voltage balance is the correct value of the square of delt_PQV- really count PQU ^ 2 the correct value of J- Jacobian matrix e- voltage real part f- the imaginary part of voltage delt_ef- voltage real part and imaginary part of the amendment value)

The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value.

基于nsga2的分时电价相关程序(考虑电动汽车负荷在内)(TOU based on nsga2)

16apsk通讯系统的信噪比与误码率计算并绘图(16APSK communications system signal to noise ratio and bit error rate calculation and mapping)