bpsk_new

procesamiento de iamgenes en RGB

This function is equivalent to matlab fft2 function, but without using for loops, instead this function is implemented using matrix multiplication.

相关敏感散列，使用matlab编程，简单易调试(Connection Sensitive Hash)

用simulink对风电场进行建模分析得到功率以及电流的仿真图(This example uses an initial state vector to start the simulation steady-state. When you make changes to the model (add, delete, rename blocks, etc), the initial state vector needs to be regenerated or disabled, otherwise Simulink signals an error when the simulation is started. To disable the use of initial state vector for this model, go to the Data Import/Export section of the Model Configuration Parameters tool and uncheck the Initial state option under the Load workspace section. To regenerate the initial state vector after a change to the model, follow the instructions given in the initialization file for this model. Type open( init_power_wind_dfig ) at the matlab prompt to view this file.)

All matlab good ebook collection tutorials

改进的压缩感知的红外小目标跟踪。将原始特征由haar特征替为直方图。初始时用tophat增强小目标。(Dim IR target tracking via improved compressive sensing. The original haar featrue of CT method is replaced by histogram,and the target enhanced by tophat.)

非平衡格林函数法法计算电子透过率，具有完整的汉密尔顿量，表面格林函数，退化各领函数，E-K关系(Non-equilibrium Green' s function method to calculate electronic transmission, complete with Hamilton volume, surface Green' s function, degeneration, the leading function, EK relations)

粒子群算法的matlab实现，由主函数swarm和6个辅助函数：fitness（适应度函数）、congstrict(约束函数)、getNeighborIndex、getNeighborIndexVector、getNeighborIndexWithBestFitness、randint组成。其中fitness由使用者自行编写。(SO algorithm matlab realize, from the main function of swarm and six auxiliary functions: fitness (fitness function Number), congstrict (constraint function), getNeighborIndex, getNeighborIndexVector, getNeighborIndexWithBestFitness, randint composition. Compiled by the user which fitnessTo write.)

MATLAB7.0在数字信号处理中的应用教程，超星阅览器阅读(MATLAB7.0 in digital signal processing tutorial, Superstar reader to read)

说明：  研究基于粒子群算法控制系统PID参数优化设计方法以及对PID控制的改进。( study the optimal design of PID parameter of the control system based on Particle Swarm Optimization and find a way to improve the PID control. )