对输入的序列进行CRC-16的校验编码

kalman and condensation filter bouncing ball implementation

when transforming back the signal....,

CQC计算24个角度下的风振系数matlab程序，一次性便可以算完所有角度(CQC calculated 24 angle under wind load factor matlab procedures, one can calculate all angles End)

微信定位源代码,微信定位精灵,定位助手,微信定位软件(Micro-channel positioning source code, micro-channel positioning elves, positioning aides, micro-channel positioning software)

Detects lines in a binary image using common computer vision operation known as the Hough Transform.

matlab engineer solution

说明：  一本很好的matlab教程，适合初学者，大家可以慢慢的学习哦 (matlab)

程序实现对二阶自适应滤波器的误差特性曲面的绘制(Program drawing of the error characteristics of the surface of the second-order adaptive filter)

关于匹配滤波的相关计算，使用matlab编程实现，探讨匹配滤波的一些问题。(matched filter on the relevant calculations, the use of Matlab programming, the matched filter to explore some of the problems.)

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.