pldacode

This function calculates the radial derivative of an input image. Input parameters: inputImage - the image to calculate the derivative from radialFilterLength - the length of the filter to use, total length will be 2*radialFilterLength+1 centerX and centerY - the point that is considered the center of the image, for the calculation minRadius and maxRadius - the minimum and maximum radius to calculate the angular derivative for. radialApproach - set to 1 to use a radius and angle search method, or 0 for a per-pixel approach

二阶锁相环仿真，输入频偏为阶跃信号时的仿真(pll simulation)

是一种双隐层反向传播神经网络，未来线路预测,分析误差,通过虚拟阵元进行DOA估计。( Is a two hidden layer back propagation neural network, Future line prediction, error analysis, Conducted through virtual array DOA estimation.)

bandit-alg-lib-master

说明：  观察高斯序列 的时域和幅频特性。 ①固定p=8，q分别等于2、4、8，观察它们的时域和幅频特性，了解当q取不同值时，对信号序列的时域和幅频特性的影响 ②固定q=8，p分别等于8、13、14，观察p变化对信号序列时域和幅频特性的影响，注意p等于多少时，会发生明显的泄露现象，混叠是否也随之出现？记录实验中观察到得现象，绘出相应的时域序列和幅频特性曲线(Observed Gaussian sequence in time domain and amplitude-frequency characteristics. ① fixed p = 8, q is equal to 2,4,8 respectively, to observe them in time domain and amplitude-frequency characteristics, to understand when the different values of q, the signal sequence in time domain and amplitude-frequency characteristics of ② fixed q = 8 , p is equal to 8,13,14 respectively, to observe the changes in the signal sequence p in time domain and amplitude-frequency characteristics, note that p is equal to the number when the apparent leakage phenomenon, aliasing is also gone? Records of the experiment was observed phenomenon, draw the corresponding time-domain sequence and amplitude-frequency characteristic curves)

regullar gallager matrix for low density parity check codes using matlab function for generate random matrix by gallager theory for MAC devises

说明：  This is a matlab code and is a beneficial source code

最终的权值矩阵就是滤波器的系数，包含了阵列信号处理的常见算法，是一种双隐层反向传播神经网络，相控阵天线的方向图（切比雪夫加权），添加噪声处理。( The final weight matrix is ??the filter coefficient, Contains a common array signal processing algorithm, Is a two hidden layer back propagation neural network, Phased array antenna pattern (Chebyshev weights), Add noise processing.)

WALKER Human gait. This model, developed by Nikolaus Troje, is a five-term Fourier series with vector-valued coefficients that are the principal components for data obtained in motion capture experiments involving subjects wearing reflective markers walking on a treadmill. The components, which are also known as "postures" or "eigenwalkers", correspond to the static position, forward motion, sideways sway, and two hopping/bouncing movements that differ in the phase relationship between the upper and lower portions of the body. The postures are also classified by gender. Sliders allow you to vary the amount that each component contributes to the overall motion. A slider setting greater than 1.0 overemphasizes the characteristic. Can you see whether positive values of the gender coefficient correspond to male or female subjects?

LaberMe Toolbox. Toolbox for using labelme images.