2-8-bit-Pipelined-ADC-Mode

利用matlab仿真软件对矩阵特征值计算的这一类算法进行了编码计算(Matlab simulation software using feature value matrix algorithm of this class of coding using)

程序功能:采用JPDA数据关联算法实现两个个匀速运动目标的点迹与航迹的关联(Program features: data association algorithm using JPDA a uniform two-point track moving objects associated with the track)

经典单相交交变换电路仿真，基于matlab7.1(Classic single-phase AC conversion circuit simulation, based on matlab7.1)

matlab和C混编，处理乘性噪声，求解变差模型。(Written by M. Kang, S. Yun, and H. Woo, the corresponding paper is "Two-level convex relaxed variational model for multiplicative denoising")

说明：  Object-oriented programming

Gradient Adaptive Laguerre Lattice Filter( Description： Implements the order recursive adaptive laguerre filter from Fejzo and Lev-Ari (1997). Advantages: *Fewer parameter to model than FIR filters modeling long impulse responses *guaranteed stability, unique global minimum, small number of parameter for prescribed modelling error *numerically robust & and low computational complexity ( O(M) ). *Fast convergence (RLS equivalent) with no apriori learning rate required *Order recursive, so filter coefficients are uncorrelated with each other, allowing for modular implementation. Setting the pole parameter to 0 yields the standard classical gradient adaptive FIR algorithm. Includes simple example on cross-talk resistant echo cancellation to show how to use it. )

没什么好东西！只是BP，PID算法而已！可以看看过得去(nothing good things! Only BP, PID algorithm! Can look at the little things)

when SNR is high , 1st sample estimator provides good estimate of A. it has no noise effect . so we don’t need averaging effect to reduce noise when SNR is high. However variance is still low in sample mean estimator which shows that in reality ,sample mean is good estimator than 1st sample estimator. So, for high SNR, we do not need to reduce the effect of noise by averaging. or we can say that for high SNR let say >1000 , 1st sample estimator got reduced noise. But as for as variance is concerned , the sample mean has low variance for high SNR as well.

SVM的SMO算法实现，svm_train为训练函数，svm_predict为预测函数，按说明输入参数即可(The SMO SVM algorithm, svm_train of the training function, svm_predict to predict function, follow the instructions to input parameters)

说明：  AR模型的大作业，涉及到2阶三阶四阶，估算AR模型的系数(AR model of operation, involving 2 third-order fourth-order, estimate the coefficient of AR model)