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用MATLAB设计IIR数字带通滤波器的程序函数(Design of IIR digital with MATLAB program function bandpass filter)

用matlab编写的车牌识别的源程序，可以准确定位到车牌(Prepared using matlab source license plate recognition, can accurately locate the license plate)

Relaying and orthogonal frequency division multiple access (OFDMA) are the accepted technologies for emerging wireless communications standards. The activities in many wireless standardization bodies and forums, for example IEEE 802.16 j/m and LTE-Advanced, attest to this fact. The availability or lack thereof of efficient radio resource management (RRM) could make or mar the opportunities in these networks. This paper therefore provides a comprehensive RRM algorithm for OFDMA-based multi-cellular fixed relay networks in a way to ensure fairness among users with minimal impact on the network throughput (in contrast, pure opportunistic RRM techniques always favor users with good channel conditions

使用LPCC参数来生成源滤波器模型的的线性预测系数(LPCC parameters to generate the linear prediction coefficients of the source filter model)

提供了一种信号频率计算算法的MATLAB实现程序(MATLAB provides a signal frequency calculation algorithm to achieve program)

基于独立成分分析的多声源分离程序包，涵盖了大部分独立成分分析的函数,经验证能够有效解决多声源分离问题。(Based on independent component analysis of multi-source separation package, covering most of the functions of independent component analysis.)

粒子滤波matlab仿真程序.粒子滤波的基本思想是：首先依据系统状态向量的经验条件分布，在状态空间抽样产生一组随机样本集合，这些样本集合称为粒子；然后根据观测值不断调整粒子的权重大小和样本位置；最后通过调整后的粒子信息修正最初的的经验条件分布，估计出系统状态和参数。该算法是一种递推滤波算法，可以用来估计任意非线性非高斯随机系统的状态和参数。 粒子滤波主要有三步基本操作：采样（从不含观察值的状态空间产生新的粒子）、权值计算（根据观察值计算各个粒子的权值）、重采样（抛弃权值小的粒子，使用权值大的粒子代替），这三步构成了粒子滤波的基本算法。 SIRF(Sample Importance Resampling Filter)算法是粒子滤波的一种基本算法。(Particle filter matlab simulation program)

this function used to calculate COFACTOR

基于matlab的无刷直流电机仿真速度PI，电流PI双闭环仿真(Matlab-based simulation of brushless DC motor, using speed PI, current PI double closed loop control.)

说明：  bpsk仿真中间有两个方面的内容，很好的仿真软件(There are two files in the zip folder. bpsk_spread.m and jakesmodel.m Steps for simulation: 1] Run jakesmodel.m first 2] Then run bpsk_spread.m . 3] Note that during the first run bpsk_spread.m has no rayleigh fading.This is because the corresponding code has been commented 4] The resulting performance is stored in BER_awgn. 5] Now uncomment the Rayleigh Fading code in bpsk_spread.m file. 6] Same time comment BER_awgn (line 112) and uncomment BER_ray variable. 7] Run the simulation. )