double-fedmachine

完整的语音识别程序，训练模型型固定。可以运行出识别结果的~ (Integrity of the speech recognition process, training the model fixed. Can run the results of the identification of ~ )

基础的的SAR成像源代码！能够实现运行，供学习参考(this is the code of sar ,it is very good!)

a lightweight implemetation of sstable and memory table like leveldb

max_line_search_3pt_equal_intervals matlab code

有关迭代法和插值法的程序。包括高斯赛德尔迭代法、牛顿迭代法、拉格朗日插值法、牛顿插值法等。(Programs about iterative and interpolation method,including Gauss-Siedel ,Newton iterative method, Lagrange and Newton interpolation method.)

说明：  最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数，即无约束优化问题时，梯度下降（Gradient Descent）是最常采用的方法之一，另一种常用的方法是最小二乘法。在求解损失函数的最小值时，可以通过梯度下降法来一步步的迭代求解，得到最小化的损失函数和模型参数值。反过来，如果我们需要求解损失函数的最大值，这时就需要用梯度上升法来迭代了。在机器学习中，基于基本的梯度下降法发展了两种梯度下降方法，分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)

分数阶傅里叶变换，主要对SAR信号进行处理，使数据处理量大大减少。(Fractional Fourier transform, mainly on the SAR signal processing, the data processing is greatly reduced.)

he power method will be applied to the jacobian matrix of the 2-D henon map to approximate the first Lyapunov exponent by creating a graph of ln|yn| vs. n, where n is the number of iterations of the power method and yn = 1/n*ln|DG^n(xo)*yo|. The slope will be an approximation to the largest Lyapunov exponent.(he power method will be applied to the jacob ian matrix of the 2-D map to approximate henon th e first Lyapunov exponent by creating a graph of ln | yn | vs. n, where n is the number of iterations of the power m ethod and yn = a/n* ln | DG ^ n (xo)* yo |. The slope w ill be an approximation to the largest Lyapunov exponent.)

仿真分析相控阵雷达中二维面阵的雷达方向图以及一些其他因素对方向图的影响，以及随机误差和量化误差的影响(Simulation analysis of radar direction Fig. 2D phased array radar array and some other factors on the direction map, and the effect of random error and quantization error)

This matlab code demonstrates independent component analysis.