CHAP2_3

用matlab实现偏微分方程的求解，具体的算法实现都以给出。(Using matlab to achieve the solution of partial differential equations, specific algorithms have to give.)

用matlab编的一个用于对统计数据进行威布尔分布的估计，并对其进行三参数的评估与计算(Matlab compiled a for the statistical data of weibull distribution estimates, and the three parameters calculation and evaluation)

利用直接法、间接法、以及Bartlett窗及Hamming窗下的Welch法进行功率谱分析(Using the direct method, indirect method， and the Bartlett window and a Hamming window in the Welch method for power spectral analysis)

Atef Elsherbeni书第一章中一个一维FDTD仿真程序实例(A one dimensional FDTD simulation example in the FDTD textbook written by Atef Elsherbeni in the first chapter.)

使用matlab来仿真，是卫星导航电文调制，扩频后，产生.mat文件(Matlab simulation satellite navigation message modulation, spreading generate. Mat file)

遗传算法优化bp神经网络，采用的是实数编码方式。(Genetic algorithm optimization bp neural network, using real number encoding.)

说明：  利用小波分析的方法，来实现数字图像的分解(using wavelet for image)

数值计算中的Euler法相关的matlab源程序(Numerical calculation of the Euler method related to matlab source)

数字信号处理的实验课件，含有matlab的各种代码，。(signal operation)

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.)