wavelet-coherence-master12

这是PSO中的流程图,用于各种PSO编程,它包含了4个.与基本的程序对照起来用比较方便.(This is a flow chart of PSO, PSO for a variety of programming, which includes 4. And basic procedures were more convenient to use.)

bp神经网络的设计 希望大家相互探讨 相互学习 (bp neural network design hope we mutually explore and learn from each other)

利用拉普拉斯变换的思想，通过对数据进行差分，近似得到拉普拉斯变换后的结果，然后检查正负交换的位置，则此为极值点位置，利用此思想得到极值点的位置。(Using the ideas of Laplace transform of the data by the difference approximation get results Laplace transform, and then check the position of the positive and negative exchange, this is the extreme position, take advantage of this thinking of getting extreme points location.)

说明：  BP_Adaboost模型即把BP神经网络作为弱分类器，反复训练BP神经网络预测样本输出，通过Adaboost算法得到多个BP神经网络弱分类器组成的强分类器，利用此方法设计出强分类器。(The BP_Adaboost model uses the BP neural network as a weak classifier, repeatedly trains the BP neural network to predict the sample output, and uses the Adaboost algorithm to obtain a strong classifier composed of multiple BP neural network weak classifiers. This method is used to design a strong classifier.)

说明：  PWM斩波控制电路的matlab/simulink仿真电路，(PWM tracking control PWMmatlab/simulink)

说明：  EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精度。 (EKF only uses non-linear function of the first-order Taylor expansion of some partial derivatives (ignoring higher order terms), often leading to the posterior distribution of the state estimates to generate large errors affect the performance of filtering algorithms, which affect the whole tracking system performance. Recently, the field of adaptive filtering algorithms and the emergence of new- and tasteless transform Kalman filter (Unscented Kalman Filter-UKF). EKF UKF filter is different from the idea that it points through the design of a small amount of σ by σ point spread through the nonlinear function to calculate the random vector first and second order statistical properties of the transmission. Therefore it is better than the EKF filter nonlinear characteristics equation of state approach, which is more than the EKF filter estimation accuracy.)

lorentz 函数拟合 (lorentz function fit)

对几个混合的常规信号进行傅里叶变换，并将其分离开。然后对几个信号进行时频分析，并求出参数估计的误差。(Conventional signals of several mixed Fourier transform, and separated them. And then the several signal time-frequency analysis, and the parameter estimation error.)

Sinus programming For Matlab

说明：  stft(含:短时傅立叶变换 Gabor变换等)(stft (containing: STFT Gabor transform, etc.))