beam_patterns2

这是一个简介sinulink的课件文档，对入门有些帮助。(This is a profile sinulink courseware documents on entry of some help.)

在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。(The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved.)

Chinese text categorization and classification of the document indexing mechanism model of

matlab program in artificial intelligent in power system optimization problem using GA

快速计算rcwa一维，投射场 衍射场分布(Rapid calculation rcwa one-dimensional projection field diffraction field distribution)

给出了基本的有监督的基于矩阵分解的链路预测的代码。(Supervised link prediction based on matrix decomposition)

说明：  matlab 图像处理程序例子 供初学者参考(matlab image processing procedure example of reference for beginners)

这是另外一个基于工序的柔性作业车间调度的程序，简单易行(This is another process based on the flexible job-shop scheduling procedures, simple)

We see that HTH matrix is almost diagonal as the off diagonal elements are nearly zero. So we are getting exact estimation in case of PRN INPUT due to diagonality of HTH matrix. As seen that the unknown inpulse response ( h ) and estimated impulse response ( hth ) are coming out to be exactly same. The estimation even gets better for large N .as we get the HTH matrix perfect diagonal. So we come to know that we can estimate the unknown parameters exactly when PRN input is used.

利用MATLAB进行数据拟合，常见的数据拟合方法。包括：一元函数插值、样条插值、多项式插值或拟合 、曲线拟合、拉格朗日插值法等。(MATLAB data fitting, common data fitting methods. It includes: interpolation of unitary function, spline interpolation, polynomial interpolation or fitting, curve fitting, Lagrange interpolation, etc.)