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％ BackgroundRemoval=[true],false ％ Gain=[tsquare],linear ％ BandPass=[paul],fircls ％ CenterFrequency, auto (determined using pburg) ％ BandWidth=auto (a fraction of the CenterFrequency default=0.25) ％ ContrastStretch=[true],false ％ HilbertAmplitude=[true],false ％ HorizontalStacking=1 (a number of traces) ％( BackgroundRemoval = [true], false Gain = [tsquare], linear BandPass = [paul], fircls CenterFrequency, auto (determined using pburg) BandWidth = auto (a fraction of the CenterFrequency default = 0.25) ContrastStretch = [true], false HilbertAmplitude = [true], false HorizontalStacking = 1 (a number of traces))

Express gatool use of MATLAB in the implementation of training neural network genetic algorithm procedure

说明：  Belief Propagation (BP) Implementations gabp.m, run_gabp.m => Gaussian BP - parallel version asynch_GBP.m => Gaussian BP - serial version sparse_gabp.m, run_sparse_gabp.m => Gaussian BP - sparse version, optimized, tested on sparse matrices gabpms.ms, run_gabpms.m => Quadratic Min-Sum algorithm - Moallemi and Van-Roy

本文件主要的功能为：图像压缩与图像共生矩阵的能量(matlab)

Check this file for sensor

进行逐步线性回归，相关分析过程的matlab方法，含噪脉冲信号进行相关检测,关于神经网络控制，各种kalman滤波器的设计，使用混沌与分形分析的例程。( Stepwise linear regression, Correlation analysis process matlab method, Noisy pulse correlation detection signal, On neural network control, Various kalman filter design, Use Chaos and fractal analysis routines.)

基于MATLAB实现了极坐标下的傅里叶变换，对一个给定 n×n 的二维信号，其计算复杂度等价于笛卡尔坐标下的2D-FFT，可广泛应用于图像处理和分析。(A fast high accuracy Polar FFT algorithm is given in the software package written in MATLAB. For a given 2D signal of size n×n, the algorihtm s complexity is just like in a Cartesian 2D-FFT, which can be used widely in image processing and analysis.)

均匀直线阵 辅助天线4路 相控阵雷达的有源旁瓣干扰对消仿真程序(sidelobe cancelation alogrithm simulation matlab code )

GPS的MATLAB仿真程序，仿真了读取导航电文信息、卡尔曼滤波、解算定位等功能。(GPS for MATLAB simulation, emulation of the read navigation data information, Kalman filter, calculate the positioning function.)

“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。(In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its local context based on a Bayesian framework, which models the statistical correlation between the low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is posed by computing a confidence map, and obtaining the best target location by maximizing an object location likelihood function. The Fast Fourier Transform is adopted for fast learning and detection in this work. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.)