ricker

Robotic Sound Source Separation using Independent Vector Analysis

盲源分离的的简单易用 适合初学者你们慢慢学习下我只能帮你到这了(signal separation snr matlab code)

最优状态估计书Ebook_Optimal_State_Estimation(Ebook_Optimal_State_Estimation)

计算小波能谱熵的资料，很有用。计算小波能谱熵的资料，很有用。计算小波能谱熵的资料，很有用。(Calculating wavelet energy spectrum entropy information useful. Calculating wavelet energy spectrum entropy information useful. Calculating wavelet energy spectrum entropy information useful.)

3维重建(MATLAB) 【浙大计算机视觉大作业】(reconstruct the 3D coordinates [the homework of the class：computer vision ZJU ])

设计一维纳滤波器 (1)产生三组观测数据：首先根据s(n)=a s(n-1)+w(n)产生信号s(n)，将其加噪（信噪比分别为20dB,10 dB，6 dB），得到观测数据x1(n), x2(n), x31(n). (2)估计xi(n)，i=1,2,3的AR模型参数。假设信号长度为L，AR模型阶数为N，分析实验结果，并讨论改变L,N对实验结果的影响。 (A Wiener filter design (1) to produce three sets of observations: first generating a signal s (n) according to s (n) = as (n-1)+w (n), to add noise (20dB SNR, respectively , 10 dB, 6 dB), to obtain observational data x1 (n), x2 (n), x31 (n). (2) estimate xi (n), i = AR model parameters 1,2,3. Assuming the signal length L, AR model of order N, analysis of experimental results and discuss the impact changing L, N of the experimental results.)

模糊熵（Fuzzy Entropy）的MATLAB程序(MATLAB codes of Fuzzy Entropy)

WAVEVIB generates a vibroseis waveform (Clauder wavelet) by ％ first calling SWEEP to generate a linear sweep and then calling ％ AUTO to autocorrelate that sweep. Theoretically, the autocorrelation ％ length is ~ 2*slength but only only the central wlength long ％ part is generated. This is like windowing the auto with a boxcar.(WAVEVIB generates a vibroseis waveform (Clauder wavelet) by first calling SWEEP to generate a linear sweep and then calling AUTO to autocorrelate that sweep. Theoretically, the autocorrelation length is ~ 2* slength but only only the central wlength long part is generated. This is like windowing the auto with a boxcar.)

It is matlab code for optimizing the function.Hear we use particle swarm optimization technique for optimization.

讲述MATLAB的使用教程，由浅入深讲解详细(About the use of MATLAB tutorial, progressive approach to explain in detail)