PIDcontorl

UN AUTRE MONDE DE LA VISION.............MATLAB..................SEGMENTATION

图像阈值分割技术在图像分割中具有重要的意义。遗传算法既可以对全局信 息高效利用，也减少了存储空间和计算量。利用遗传算法的优点，提出了一 种用改进遗传算法的图像分割的方法，可以将父代中适应度大的个体代替当前代 中的个体，保证了可以选出最优的个体。遗传算法是具有鲁棒性和自适应性的搜 索方法.通过实验对比，表明该方法具有快速、稳定分割的特点。(Image threshold segmentation technology is of great significance in image segmentation. Genetic Algorithms can be used for global information Efficient utilization of information also reduces storage space and computation. Based on the advantages of genetic algorithm, a new genetic algorithm is proposed. A method of image segmentation based on improved genetic algorithm can replace the current generation with individuals with large adaptability in the parent generation. The individual in the system ensures that the best individual can be selected. Genetic Algorithms are Robust and Adaptive Search The experimental comparison shows that the method has the characteristics of fast and stable segmentation.)

A working setup that focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [

DOA估计中，2MUSIC算法的前后向平滑与前向、后向平滑的比较。(This is the DOA estimation by ULA and spatial smoothing.)

discrete-time transfer function to approximate

说明：  time series prediction codes. for arma and ar modelling

有关SLM的调制方式，希望大家好好学习，天天向上，努力提高自己(SLM modulation on, I hope you study hard, every day, strive to improve their)

Face Recognition system

Comparacion del BER de un canal AWGN y Rayleigh en matlab. 100 bien

使用MATLAB实现的基于多类别的KNN算法，简称为MLKNN(Using MATLAB to achieve KNN algorithm based on multi-category, referred to as MLKNN)