ex05

here are all the turbo codes in matlab where to the final of the simulation make a comparation of the S/N of each one of the models

学习的一个产物，供大家作为实验的参考，不好的地方见谅(A product of learning for us as a reference experiment, where poor excuse me)

A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.

MATLAB/SIMULINK BASED NON Linear Control of PUMA 560

<Synthetic Aperture radar Signal Processing with Matlab Algorithms>的matlab代码。(the source of "<Synthetic Aperture radar Signal Processing with Matlab Algorithms>)

在matlab软件平台上对一些需要调用的特殊函数的计算。(Special function calculation)

添加噪声处理，用于时频分析算法，实现六自由度运动学逆解算法。( Add noise processing, For time-frequency analysis algorithm, Six degrees of freedom to achieve inverse kinematics algorithm.)

说明：  实现BP分类，利用PSO优化BP，换数据可直接运行(Realize BP classification, use PSO to optimize BP, change data to run directly)

matlab命令大全。姚东，王爱民，冯峰，王朝阳等编著(matlab command Daquan. Yao Dong, Wang Aimin, Feng Feng, Chao-Yang Wang, eds)

Digital modulation techniques