ASK_FSK_PSK

Max-Min Algorithm for grid scheduling

格子boltzmann 方法，D2Q9模型，圆柱绕流，采用反弹-漫反射综合边界条件(Lattice boltzmann method, D2Q9 model flow around a cylinder, using the bounce- Diffuse integrated boundary conditions)

对一维信号采样并进行傅里叶变换画出频谱图。(Sampling and Fourier transform draw spectrum diagram of one-dimensional signal.)

将基带信号输入序列，对应输出AMI,CMI,HDB3和双向码序列以及波形(The baseband signal input sequence corresponds to the output AMI, CMI, HDB3 and bidirectional code sequence and waveform.)

离散Hopfield神经网络的分类-高校科研能力的评价，有Hopfield神经网络的详细的M文件程序，适合初学者(Discrete Hopfield neural network classification- the evaluation of university research capacity, the Hopfield neural network of the M-file program, suitable for beginners)

信道是多径信道,升余弦滚降 ，取样时间无偏差的信道特性,与波形功率谱,与误码率仿真(Channel is multipath channel or Cosine, sampling time without deviation channel characteristics, and power spectral waveform, with BER simulation)

基于mit数据库的时域心率算法，阈值自动更新，心率自动计算。(Mit database based on time-domain heart rate algorithm, the threshold value is automatically updated, heart rate calculated automatically.)

地球物理大地电磁测深一维正演，是求解析解(magnetotelluric 1D forward)

matlab lms code whaich is used for echo cancellation

说明：  盲源分离FastICA、matalab程序，(FAST KERNEL ICA | |--------------------| Version 1.0- February 2007 Copyright 2007 Stefanie Jegelka, Hao Shen, Arthur Gretton This package contains a Matlab implementation of the Fast Kernel ICA algorithm as described in [1]. Kernel ICA is based on minimizing a kernel measure of statistical independence, namely the Hilbert-Schmidt norm of the covariance operator in feature space (see [3]: this is called HSIC). Given an (n x m) matrix W of n samples from m mixed sources, the goal is to find a demixing matrix X such that the dependence between the estimated unmixed sources X *W is minimal. FastKICA uses an approximate Newton method to perfom this optimization. For more information on the algorithm, read [1], and for more information on HSIC, refer to [3]. The functions chol_gauss and amariD are taken from and based on, respectively, code from Francis Bach (available at http://cmm.ensmp.fr/~bach/kernel-ica/index.htm). The derivative is com)