mimo2x2_BSPSK.m

说明：  一个新的智能算法Free Search的Matlab源码(A new intelligent algorithm Free Search of the Matlab source)

说明：  G。729算法的MATLAB程序实现，用于算法仿真(G。729)

信号的时域运算、时域变换及MATLAB实现(Signal in the time domain operation, the time domain transformation and MATLAB )

本程序提供了一维、二维、三维插值算法的MATLAB源代码(This program provides a one-dimensional, two-dimensional, three-dimensional interpolation algorithm MATLAB source code)

画出边缘列表画出边缘坐标列表边缘分割边缘佳策边缘提取(Draw the edge of a list of coordinates to draw the edge of the edge list of partition the edge of good strategy Edge)

Matlab OFDM MIMO channel responses antennas

Design tools have been developed based on image processing models to design and validate the navigation functions regarding performances and robustness

神经网络小波变换的MATLAB编程，用于实现其二维图像的小波变换处理(Neural network wavelet transform MATLAB programming for the realization of the two-dimensional image of the wavelet transform)

根据PSO算法原理，在MATLAB中编程实现基于PSO算法的函数极值寻优算法，程序前面给出了PSO算法参数设置，种群初始化，寻找初始极值，迭代寻优，最后通过算法反复迭代300次，画出每代最优个体适应度值变化曲线，最后通过对比发现说明PSO算法具有较强的函数极值寻有能力，谢谢，希望对大家有帮助。 (According to the principle of PSO algorithm in MATLAB programming function PSO algorithm based on extreme value optimization algorithm, the preceding program gives the PSO algorithm parameter settings, population initialization, looking for initial extreme value, iterative optimization, and finally through the iterative algorithm 300 times draw the best individual fitness value of each generation curve, and finally by comparing the findings indicate that PSO algorithm has strong function extreme ability to find, thank you, we want to help.)

ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。 基本思想： 在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。 (Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach. Basic idea: The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions. After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour. Literature: - Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I)