2D-variogram

详细讲述了直接序列扩频差分锁相环的文章，包含具体的算法结构，并附有仿真结果。(A novel differentially coherent delay-locked loop(DCDLL) for accurate code tracking is proposed for direct sequence spread spectrum systems. Due to the use of the differential decoder and exactly one correlator, the proposed scheme avoids the problems of gain imbalance. The tracking error variance is derived by linear analysis. When the proposed DCDLL scheme is applied in ranging with additive white Gaussian noise (AWGN) channel, the performance of the proposed DCDLL scheme is about 1.4 dB better than that of one-correlator tau–dither loop (TDL), and near that of noncoherent DLL.)

自己按照下载的信号发生器源程序编写调试，调试成功(Signal generator in accordance with their own source code download write debugging, debugging success)

The first scheme is based on the spatial locality of feature vectors corresponding to similar images. Learning is effected by modifying the query vector to incorporate the positive examples. The second scheme is based on “distorting” our view of the feature space. An new similarity distance between an image and the query is learned from the relevance feedback.

实现彩色图象的读取,以及回度图象的读取,及相关的变换(Achieve color image reading, and reading back of the picture, and the associated transformation)

压缩感知理论和应用，介绍基本理论和方法，入门书(Compressive Sensing- Theory and Application)

Cao法求嵌入维数ｍ，相空间重构理论需计算最优嵌入维数ｍ和最佳延迟时间τ, 重构相空间。(Cao method of embedding dimension of phase space m, to calculate the optimal embedding dimension m and the optimal time delay of phase space reconstruction theory.)

基于蚁群算法的路径规划，包括二维路径和三维路径，非常实用，无BUG，注释详细(Path planning, ant colony algorithm, including 2D and 3D path planning path,)

Hello everybody,I am MAO,I am studying Least mean square algorithm right now.

显示进程列表，PID等相关信息，是初识windows进程编程的好材料(list shows the process, PID, and other relevant information, recognize the windows of the programming process good materials)

粒子滤波跟踪算法学习的好文档。为个人读书心得，主要从三个角度去理解粒子滤波，由浅入深，有学习价值！(Particle filter tracking algorithm to learn a good document. For personal reading experience, mainly from the three perspectives to understand the particle filter, Deep learning value!)