State-Space

卫星通信系统格状编码调制，附有详细文档和源码(Satellite communication systems trellis coded modulation, with detailed documentation and source code)

基于Matlab的时域卷积的动态演示的实现，对进行DSP工作的通知可能有一定帮助。欢迎下载(Matlab-based time-domain convolution of the realization of the dynamic presentation of the work carried out to inform the DSP may have some help. Welcome to download)

T=[1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] 输入向量的最大值和最小值 threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net=newff(threshold,[31 3],{ tansig , logsig }, trainlm ) 训练次数为1000，训练目标为0.01，学习速率为0.1 net.trainParam.epochs=1000 net.trainParam.goal=0.01 LP.lr=0.1 net = train(net,P,T) 测试数据，和训练数据不一致 P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 (T = [1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] ' of the maximum and minimum input vector threshold = [0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net = newff (threshold, [31 3], {' tansig' , ' logsig' }, ' trainlm' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 )

smoothing images processing

用于提取LPC参数的MATLAB程序，并通过MATLAB展示出参数图形。(MATLAB program used to extract the LPC parameters, and by the graphics of MATLAB demonstrated parameters.)

QAM,PSK,DPSK,FSK,MSK调制仿真，包括眼图输出，误码率输出，星座图，频谱，及实际wav文件的调制解调(QAM, PSK, DPSK, FSK, MSK modulation simulation, including eye diagram output, the output BER, constellation, spectrum, and actual modem wav files)

利用matlab写成的窄带噪声发生，使用高阶累积量对MPSK信号进行调制识别，通过虚拟阵元进行DOA估计。( Using matlab written narrowband noise occurs, Using high-order cumulants of MPSK signal modulation recognition, Conducted through virtual array DOA estimation.)

粒子群算法，用于聚类.粒子群在迭代进行的过程中有可能出现早熟收敛 的问题而陷入局部最优解,因此文中在 PSO 算法部 分,设置两个变量对每个粒子和粒子群的状态进行实 时地监控,以便当检测到粒子或粒子群出现早熟收敛 现象时,能及时地对其进行变异操作,增加粒子的多样 性,使其跳出局部极值的束缚,在多维解空间中开始新 的搜索(C_PSO used for clustering)

说明：  由差分方程得到信号的冲激响应，得到连续信号的幅频相频响应(Impulse response of signal from difference equation)

matlab for Lattice Boltzmann