jengqen_v26

对图像的小波分解与重构，并且进行阈值滤波，对滤波前后的图像进行了对比(The image of the wavelet decomposition and reconstruction, and the threshold to filter the images before and after filtering were compared)

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.

An introduction of digital signal processing with matlab

Matlab中的模型预测控制工具箱英文详细介绍。(Model predictive control toolbox of Matlab detailed introduction in English.)

current calculation maTLAB FILE

matlab projects, histogram equalization

随机权重粒子群算法，来自来自于《精通MATLAB最优化计算》( pso with random weight)

模糊控制系统设计，用matlab语言实现系统设计(Matlab language used fuzzy control system design)

以某化工厂生产过程中的70个产量数据为例，用matlab编程进行分析(Taking a chemical plant in the production process 70 production data, for example, an analysis using matlab programming)

基于Matlab的一种光伏阵列模拟器的研究(matlab)