ivt-2008-05-04

使用自然梯度盲分离算法，实现对四个亚高斯信号的分离，并从分离结果可总结出盲分离算法的两个不确定性。同时给出了串音误差。(Blind separation using the natural gradient algorithm to achieve the separation of the four sub-Gaussian signals, and the separation results can be summarized from the blind separation algorithm of two uncertainty. Crosstalk error is also given.)

simulation UPQC in matlab using state space model

在MATLAB中建立基于VSG控制方法下的孤岛模式下带负载稳定运行(The load stable operation with VSG control based on the island)

（1）编程建立Gold序列，仿真Gold序列的波形； （2）仿真Gold序列的自相关和互相关特性。 （3）编程仿真直接扩频通信系统模型，画出扩频前后信号波形及频谱。((1) programming Gold sequence and simulating the waveform of Gold sequence; (2) the autocorrelation and cross correlation characteristics of the simulated Gold sequences. (3) programming direct spread spectrum communication system model, draw the signal spectrum and spectrum before and after spread spectrum.)

MATLAB ask psk fsk dpsk调制解调

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

灰度共生矩阵提取纹理特征可用于图像纹理特征提取(GLCM texture)

ofdm的基本原理 及MATLAB仿真(ofdm simulation of the basic principles and MATLAB)

matlab源代码，是非负矩阵分解工具箱，包含乘法更新，最小二乘约束，投影梯度法等方法(Usage: [W,H] = nmf(X,K,alg,maxiter,speak) W: output matrix H: output matrix X: input matrix K: number of components alg: algorithm to use maxiter: maximum number of iterations speak: print to screen Algorithms: mm: Multiplicative updates method using euclidean distance measure. cjlin: Projected gradient method prob: Probabilistic non-negative matrix factorization. als: Alternating least squares. alsobs: Alternating least squares with optimal brain surgeon. Demonstrations: PET: NMF on a PET dataset Text: NMF used on a three different datasets Email, medical, and CNN. Algorithms mm: Multiplicative update method using euclidean distance measure. Described in Lee and Seung, 2001, Algorithms for Non-negative Matrix Factorization, Advances in Neural Information Processing Systems 13, 556-562. This algorithm is the most commonly used algorithm to solve NMF. cjlin: Alternative non-negative least squares using projected gradients. Author: Chih-Je)

采用希尔伯特黄变换对几组原始健康数据进行损伤检测等模拟(Hilbert Huang transform is used to simulate several groups of original health data.)