rgkutt

《MATLAB 7.X程序设计》-王建卫-源代码及习题答案(" MATLAB 7.X program design" - Wang Wei- the source code and answer exercises)

把微分方程的一维经典初值问题的有限插分法：Euler法、改进的Euler法、Admas二步外插法、Admas二步内插法编写成通用子程序，并且利用这些通用子程序解决常微分方程的数值解。(The classical one-dimensional differential equations initial value problem of limited interpolation method: Euler method, improved Euler method, Admas outside the two-step interpolation, Admas two-step interpolation method into a general-purpose subroutine to prepare and use it to solve common subroutines Numerical Solution of Ordinary Differential Equations.)

说明：  这是求解连通图的最小生成树的一种经典算法：Kruskal 算法！值得推广，还带例题哦!(This is a connected graph of the minimum spanning tree for solving a classical algorithm: Kruskal algorithm! Worth promoting, but also with examples Oh!)

神经网络的应用书籍源码，想学习的的的同学拿去吧(The application of neural network book source code, want to learn the students take it)

this is about 2 x 2 mimo ofdm

利用偏最小二乘法实现对近红外光谱的血液定量分析(Quantitative analysis of blood in near infrared spectrum by partial least squares)

第二代小波提升变换源码，呵呵呵呵呵，大家多交流啊，欢迎大家 (Second Generation Wavelet Transform source upgrade, huh, huh huh Oh, we more exchanges ah, welcome to)

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.)

线性调频信号的时域，频域表示，包括坐标转换设置。对雷达初学者有指导意义！(Linear FM signals in time domain, frequency domain representation, including coordinate conversion settings. Radar beginners guide!)

Support Vector Machine KM matlab code