电力线噪声模型仿真

fastica用于信号处理，好用的工具包(FastICA for signal processing, use the toolkit)

基于db2小波包的信号分解，便于理解，方便阅读(Db2 wavelet packet-based signal decomposition, easy to understand, easy to read)

针对多目标测控问题，提出了一种实用的利用基于圆阵的数字波束形成技术来实现目标跟踪的系统。在系统实际工作于噪声和干扰环境中时，为避免计算梯度时可能出现的数值突变，提出了一种修正的梯度跟踪自适应算法，可靠地实现了权值更新，并对各阵元输出进行加权合并，以获得最大信号输出，同时实现对目标方位角和俯仰角的自动捕获和跟踪，且跟踪迅速、正确、稳定。仿真结果表明了所提出的方案的正确性。(Monitoring and control for multi-objective problem, a practical circular array-based digital beam forming technology to achieve target tracking system. Practical work in the system noise and interference in the environment is investigated in order to avoid calculate the gradient values may be mutations present a modified gradient tracking adaptive algorithms, reliably achieve the right value update, and the output of the array weighted combined to obtain maximum signal output, while achieving the target azimuth and elevation of the automatic capture and tracking, and tracking fast, accurate and stable. Simulation results show that the proposed scheme is correct.)

FM_DCSK的matlab源程序，相互学习使用(FM_DCSK matlab source, learn from each other using)

模式识别课程中的主成分分析方法PCA的matlab实现源码(Pattern Recognition in the principal component analysis PCA matlab to achieve source)

利用FFT快速计算，线性排列阵子方向图。( This function computes and returns the gain radiation pattern for a linear array It uses the FFT to computes the pattern *INPUTS********** Nr ==> number of elements dolr ==> element spacing (d) in lambda units divided by lambda theta0 = steering angle in degrees winid ==> use winid negative for no window, winid positive to enter your window of size(Nr) win is input window, NOTE that win must be an Nr X 1 row vector nbits ==> number of bits used in the pahse shifters negative nbits mean no quantization is used *OUTPUTS****************** theta ==> real-space angle patternr ==> array radiation pattern in dBs patterng ==> array directive gain pattern in dBs ***************************************** )

对线性时变模型和非线性模型的预测控制算法进行了仿真分析，设计了两种模型下的模型预测控制的实现(Simulation analysis of linear time-varying model and nonlinear model predictive control algorithm)

分析了该信号的时域、频域、倒谱，循环谱等,小波包分析提取振动信号中的特征频率，各种kalman滤波器的设计。( Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. Wavelet packet analysis to extract vibration signal characteristic frequency, Various kalman filter design.)

说明：  利用小波方法对语音信号进行去噪，取得了很好的效果。(using wavelet method of voice signal denoising, and achieved very good results.)

说明：  PSO算法，通用性较强，只要换一下fitness就可以了(PSO algorithm, universal strong, as long as a change in fitness can be a)