MJchangeN

this a bank acount projet for back and work like a bank

CONTROLLER DESIGN FOR TIME DELAY SYSTEMS,

说明：  MATLAB及在电子信息课程中的应用,电子工业出版社出版 陈怀琛 吴大正 高西全合著(MATLAB and courses in electronic information, the application Electronics Industry Publishing House Huai-WU West are all co-)

基于麦克风十字阵列的波速形成二维空间的声源定位(Forming a sound source localization based on two-dimensional space velocity microphone array Cross)

experiments of lab 2 in digital signal processing

哈弗曼编码用MATLAB语言和C语言来解释(Huffman coding using MATLAB and C language to explain)

matlab高级图形界面设计实例，文件中包含了两个matlab GUI 实例(matlab graphical interface design example, the file contains two Matlab GUI instances)

RSSI仿真定位算法 ，使用RSSI算法进行定位( RSSI location algorithm simulation, using the RSSI algorithm to locate)

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)

《现代通信系统》matlab版第二版pdf文档(" Modern communication systems" matlab version of the second edition pdf documents)