cdma.recove

number addition java codes

说明：  牛顿插值法，是学习插值的基本内容，这里是一个该插值法的matlab程序文件，可以帮助大家进一步学习(Newton interpolation, interpolation is to learn the basic content, here is a program of the interpolation matlab file, you can help us to further study)

读取气象雷达基数据（SA），能够实现产品显示和二次处理(Read the meteorology of Base data (SA), to be able to display and secondary treatment)

Smith控制 对于系统的延迟现象 有很好的控制 使之成为一个线性系统(Smith control the delay of the system have good control so that a linear system)

LLE是一种很常用的降维方法，这是用matlab实现的(LLE is a very popular dimensionality reduction method, the code implemented using matlab)

直流电机PI调节simulink文件,有助于初学者学习matlab建模(Direct motor PI control simulink document)

说明：  通过CFAR算法实现船舶目标检测，能够得到很好地效果。(Ship target detection by CFAR algorithm)

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):

基于全相位频谱分析的相位差频谱校正法.PDF(Phase Difference Correcting Spectrum Method Based on All-phase Spectrum Analysis)

最小均方（LMS）自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的，依据输入信号在迭代过程中估计梯度矢量，并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法，其显著的特点是它的简单性。这算法不需要计算相应的相关函数，也不需要进行矩阵运算。(Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation.)