shuzixinhao2

fcnFrostFilter performs noise filtering on an image based on an adaptive filter proposed by Frost. [1] V. S. Frost, et al., "A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise," IEEE Trans. Pattern Anal., Machine Intell., vol. 4, no. 2, pp. 157-166, Mar. 1982.

基于MATLAB差分进化算法的优化问题求解程序，算法内容及结果。(MATLAB offset optimization problem solving program based on evolutionary algorithm, algorithm of contents and results.)

对某个三维集合体进行matlab重积分计算(Double integral calculation )

iteration des berfungsi untuk apa aja asal donlod

说明：  实现信号的功率谱估计，AR,MUSIC,FFT,周期图法(Achieve signal power spectrum estimation, AR, MUSIC, FFT, periodogram)

硕士学位论文捷联惯性系统初始对准研究 惯导系统的初始对准是影响系统使用性能的关键技术之一，对准的精度与速度直接关系到惯性统的精度与启动特性。对卡尔曼滤波及其在初始对准中的应用进行了研究。首先介绍了卡尔曼滤波理论的应用背景，然后推导了离散卡尔曼滤波方程，并对连续系统的状态方程进行离散化提出了适用于舰载捷联惯性系统的动基座对准的2通道10个状态变量和2通道12个状态变量的系统动态模型，并建了相应的速度匹配和位置匹配量测模型。 (master's degree thesis SINS initial alignment study INS initial alignment is affecting system performance one of the key technologies, the alignment precision and speed is directly related to the precision inertial reunification with the startup characteristics. The Kalman filter and the initial alignment of the study. First introduced the theory of Kalman filtering background, and then reasoned a discrete Kalman filter equations, also for the state of discrete equations apply to the carrier SINS System Moving Base Alignment of two channels 10 state variables and two 12-channel system state variables dynamic model and built a corresponding speed matching and position matching measurement model.)

卡尔曼滤波器在目标追踪上的应用，目标真实运动为匀速直线运动，系统噪声为高斯白噪声。(Kalman filter for target tracking application on the target real motion is uniform motion, the system noise is Gaussian white noise.)

采用MATLAB语言编译的线性方程组求解函数，希望对大家有用(resolving overdetermined linear equations)

Matlab genetic algorithm to achieve the maximum and minimum demand function problem, this paper describes the procedures for all functions matlab source code for reference

稀疏分量分解。 function [y A]=sparseBSS1(X,L,langda,G,h,delta)(function [y A]=sparseBSS1(X,L,langda,G,h,delta) ---------------------------------------------------------------- 2009-04-15 YangZhicong X: observed signal,each row correspond to a sensor observations L: the length of FFT (or the length of Hanning window) langda: adjust the desired angular width G: discretize the potential field by taking a sample of G points h: threshold y: estimated sourses A: estimated mix matrix )