magnetic_frill

能够进行电弧特性的仿真，对接地故障有一定的参考价值和意义(It can simulate the arc characteristics and has certain reference value and significance for ground faults.)

In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal frequency-division multiplexing (OFDM) block having a tile structure in the frequency domain is proposed to perform synchronization. Timing offsets are estimated using correlation-type algorithms. By inserting some null subcarriers in the proposed tile structure, we propose a computationally efficient subspace decomposition- based algorithm for CFO estimation. The issue of optimal tile length is studied both theoretically and through simulations. By judiciously designing the tile size of the pilot, the proposed algorithms are shown to have better performance, in terms of synchronization errors and bit error rate, than the time-division multiplexing-based training method and the computationally demanding space-alternating generalized expectation-maximization

直方图的仿真，直方图的仿真，直方图的仿真，直方图的仿真，(Histogram of the simulation, the simulation histograms, the histogram of the simulation, the simulation histograms,)

A method is presented for augmenting an extended Kalman filter with an adaptive element. The resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics.(A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics .)

极限学习机极速学习机\ELM 稀疏表示人脸识别稀疏表示\L0范数求解L1范数ELM神经网络AR人脸数据库基于ELM的图像分类与稳健回归算法研究基于ELM与稀疏表示的混合人脸识别算法 AR人脸识别准确率0.95. 文章:Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artificial Intelligence 27 (2014): 228-235.(Matlab codes of the following paper: Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artificial Intelligence 27 (2014): 228-235.)

说明：  ELM算法可以实现鸢尾花分类，同时实现其他数据的回归(ELM relasized iris recognition and other regression)

matlab的图像教程，很好的资料，有很多例子(matlab image tutorial, good information, there are many examples)

MATLAB实现数字FIR的高通_和带通等滤波器的源程序(MATLAB implementation of digital FIR high-pass and band-pass filters _ source program)

实现数据的预测 通过建立模型 训练模型 从而生成arma模型 达到预测(make prediction)

基于adaboost的人脸检测算法,包括训练，修改了数据读取结构，降低了内存需求(Based on adaboost face detection algorithms, including training, to modify the data read structure, reducing the memory requirements)