Patent-Emerson

power flow test para melhorar a sua compreenç ã o desta dificil tarefa q sacanagem!!

电动汽车充电功率需求的统计学建模方法，可以看看喔(Electric vehicle charging power requirements of the statistical modeling methods, you can see Oh)

DFT数字信号采集滤波器实例演示程序，很实用的一个小程序。(DFT filter digital signal acquisition example demo program, it is a small utility program.)

说明：  最大熵准则图像分割,matlab程序互相学习一下(Maximum entropy image segmentation, matlab program learn from each other about)

模拟退火算法的基本思想是从一给定解开始,从邻域中随机产生另一个解,接受Metropolis准则允许目标函数在有限范围内变坏,它由一控制参数t决定,其作用类似于物理过程中的温度T,对于控制参数的每一取值,算法持续进行“产生—判断—接受或舍去”的迭代过程,对应着固体在某一恒定温度下的趋于热平衡的过程,当控制参数逐渐减小并趋于0时,系统越来越趋于平衡态,最后系统状态对应于优化问题的全局最优解,该过程也称为冷却过程,由于固体退火必须缓慢降温,才能使固体在每一温度下都达到热平衡,最终趋于平衡状态,因此控制参数t经缓慢衰减,才能确保模拟退火算法最终优化问题的整体最优解。(Simulated annealing algorithm based on the idea that a given solution from the beginning, randomly generated from the adjacent domain to another solution, Metropolis acceptance criteria for the objective function to allow a limited range of deterioration, which is a control parameter t decided that its role is similar to the physical the course of the temperature T, the control parameters for each value, the algorithm continued to "have- to determine- to accept or rounding" of the iterative process, corresponding to a solid at a constant temperature of the process tends to thermal equilibrium, when control parameters and tended to decrease gradually 0:00, the system equilibrium state more and more, and finally the system state corresponds to the optimization problem of global optimal solution, the process is also known as the cooling process must be slow as a result of annealing temperature of solid to make solid temperature in each of them had attained thermal equilibrium, and ultim)

ofdm系统功能模块仿真（包含信道误码率等）(ofdm simulation system modules (including the bit error rate, etc.))

matlab遗传算法实例,用于在matlab环境下遗传算法的实现.(Matlab GA example, for the Matlab environment genetic algorithm.)

Matlab program for interfacing parallel_serial_port.................

压缩采样仿真实验代码，基于随机解调器，仿真功能完善(Compressive sampling simulation code, based on random demodulator perfect simulation function)

梯度下降法是一個一階最佳化算法，通常也稱為最速下降法。 要使用梯度下降法找到一個函數的局部極小值，必須向函數上當前點對應梯度（或者是近似梯度）的反方向的規定步長距離點進行疊代搜索。如果相反地向梯度正方向疊代進行搜索，則會接近函數的局部極大值點；這個過程則被稱為梯度上升法。(The gradient descent method is a first-order optimization algorithm, also commonly referred to as the steepest descent method. To find the local minimum of a function using the gradient descent method, an iterative search must be performed to the specified step distance point in the opposite direction of the gradient (or approximate gradient) of the current point on the function. If the search is reversed in the opposite direction to the positive direction of the gradient, it will approach the local maximum point of the function; this process is called the gradient ascent method.)