MATLAB

％ ％ set some variables in the workspace to control behaviour: ％ ％ graphicsMode 0 no graphics, ％ 1 graphics, particles, beacons, ground truth ％ 2 graphics, as above + range circles ％ ％ perfect 0 use beacon range data ％ 1 use ground truth range data ％ clear a( Set some variables in the workspace to control behaviour: graphicsMode 0 no graphics, 1 graphics, particles, beacons, ground truth 2 graphics, as above+ Range circles perfect 0 use beacon range data 1 use ground truth range data clear a)

Sphit算法针对１２８*１２８的灰度图象进行压缩处理，经典算法，可以任意改进()

This Matlab Code models a Rayleigh fading channel using a modified Jakes channel model. A modified Jakes model chooses slightly different spacings for the scatterers and scales their waveforms using Walsh–Hadamard sequences to ensure zero cross-correlation. alpha_n = frac{pi(n-0.5)}{2M} and eta_n = frac{pi n}{M}, results in the following model, usually termed the Dent model or the modified Jakes model: R(t,k) = sqrt{frac{2}{M}} sum_{n=1}^{M} A_k(n)left( cos{eta_n} + jsin{eta_n} ight)cos{left(2pi f_d t cos{alpha_n} + heta_{n} ight)}. The weighting functions A_k(n) are the kth Walsh–Hadamard sequence in n. Since these have zero cross-correlation by design, this model results in uncorrelated waveforms. The phases ,! heta_{n} are initialized randomly and have no effect on the correlation properties. Matlab fast Walsh-Hadamard transform function is used to efficiently generate samples using this model.

基于累计量的独立分量分析的改进算法，该算法以同时对角化三阶和四阶累计量来实现盲分离．(Cumulant-based independent component analysis of the improved algorithm, which at the same time a third-order diagonalization and fourth-order cumulant to achieve blind source separation.)

image mosaicing functions

说明：  船舶z型实验 simulink仿真框图，比较实用的经典模式。希望可以帮助大家！(very good！)

Signal Processing in MATLAB

语音小波去噪方法的matlab实现 比较基础 可以看看(Voice Wavelet Denoising matlab can look at the basis for comparison)

support vector pso examples

利用留一交叉法计算数据的准确性。是处理小样本问题常用的方法之一，(Leave a calculated use of cross-data accuracy. One common method of dealing with small sample size problem,)