UCari

基于MUSIC的空间谱估计算法。使用均匀线阵。提供了解相干信号的前向平滑，双向平滑算法。(MUSIC spatial spectrum estimation algorithm. Using uniform linear array. Understand the coherent signal smoothing, double smoothing algorithm.)

matlab在计算行业中的具体应用，matlab说明(The design of a distributed MATLAB-based environment for computing pseudospectra )

带通和带阻滤波器的设计，包含原始信号，编码，以后仿真之后的信号(a design for filter,and including original signal and the image after simulation.)

OFDM Matlab/Simulink simulation Module

计算“高位平面图像”的伪Zernike矩（低 6阶），并作为特征。(Computing " high dimensional images," the pseudo-Zernike moments (low order 6), and as a feature.)

lssvm辨识系统逆模型 采用最小二乘支持向量机工具箱(lssvm identifine the pozitive model)

语音减噪，自适应滤波器减噪，谱减法减噪，维纳滤波法减噪等(Voice noise reduction, the adaptive filter, noise reduction, and reduce the noise spectrum subtraction, wiener filtering method of noise reduction, etc)

说明：  Code to use image segmentation via Graph cut

code to calculate an image saliency map

说明：  每个传感器具有一定的范围和精度，而且周围环境可能对它们产生干扰。即单传感器只能提供部分不精确的信息，从而不能排除对外界环境描述的歧义性。鉴于各传感器性能上的差异表现出的互补性，如果综合各个传感器的信息，就能得到比单一传感器所能提供的更准确可靠的信息。简言之，与单一传感器相比，多传感器数据融合由于信息的冗余性和互补性存在很多方面的优势。 多传感器融合(Each sensor has a certain range and accuracy, and the surrounding environment may interfere with them. That is to say, a single sensor can only provide some inaccurate information, so it can not rule out the ambiguity of the description of the external environment. In view of the complementarity of the differences in the performance of each sensor, if we synthesize the information of each sensor, we can get more accurate and reliable information than a single sensor can provide. In short, compared with a single sensor, multi-sensor data fusion has many advantages due to the redundancy and complementarity of information.)