IEEE14

结构力学连续梁节点弯矩求解，用于求解静定或者超静定梁的内力。(Structural Mechanics continuous beam bending moment for solving the node for the solution of statically determinate or statically indeterminate beam internal forces.)

多井下的RAKE接收机的接受性能matlab仿真源程序，可以直接运行。(RAKE receiver more than the acceptance of underground performance simulation matlab source, can be directly run.)

基于matlab的几种语音信号端点检测方法(Several based on matlab voice signal endpoint detection method)

图像协同显著性检测，用于寻找突出目标，以便于进一步分割或者检索等。(cosaliency detection for image to search for salient object in order to segment or retrieve images.)

LAMDA方法，进行模糊度解算前降低相关性处理(LAMDA for decorrelation of ambiguity resolution)

里面有三个二维模糊调节器分别实现PID控制器的参数Kp，ki，Kd，的调节。其控制原理：根据前面的偏差e和偏差变化ec将三个模糊控制器FC1,FC2,FC3分别进行模糊化，模糊逻辑推理，解模糊化。最后得到pid控制器参数调节量。(There are three-dimensional fuzzy regulator PID controller parameters Kp, ki Kd, adjust. The control principle: the front of the deviation e and error change ec three fuzzy controllers FC1 has FC2, FC3, fuzzification, fuzzy logic inference, defuzzification. Finally, get the pid controller parameter adjustment.)

使用基于峭度的FASTICA盲分离算法，实现对四个亚高斯信号的分离，并从分离结果可总结出盲分离算法的两个不确定性。(FASTICA kurtosis-based blind source separation algorithm, to achieve the separation of the four sub-Gaussian signals, and the separation results can be summarized from the blind separation algorithm of two uncertainty.)

Clark变换与Inv_Clark变换，引入输入信号进过测试能够实现功能(Clark and Inv_Clark)

1. Extract files and run Audio_denoise_main.m file folder... 2. Click on Load & play Audio file and Original sound.wav file 3. Then using slider AWGN (White gauusion noise)...it is vary 1 to 10 set it to 10.. 4. now click on Add Noise and play... 5. u can save noisy signal by save noisy signal tab... 6. now wavelet... 7. thresholding.. 8. now click on Denoise and play....wait for some time...this will take 25 sec time 9. now save that denoised signal...and record all output parameters... 10. now click on clear all and exit

小生境遗传算法用于优化问题，得到了比遗传算法更好的效果(Niche genetic algorithm for optimization problems, get better results than the genetic algorithm)