搜索资源列表
VTB4Matlab
- 一组图象与视频处理C/C++代码,该软件包可用于Matlab。包括读取AVI和CIF/QCIF视频序列代码，Canny算子，Harris角点检测，全局阈值算法，动态阈值算法等等。-AP as a video processing with C / C code, the software can be used in Matlab. AVI including reading and CIF / QCIF video sequence code, Canny operator, Harris c
ANewC4.5alg
- 经典的数据挖掘分类算法，由ID3算法演变而来。本算法主要用于处理连续属性值，基本过程如下： 1.根据属性的值对数据集排序 2.用不同的阈值将数据集动态的分类 3.迭代根据阈值进行划分 4.得到所有可能的阈值、增益以及增益比-classical classification of data mining algorithms, evolved from the ID3 algorithm. This is mainly used to deal with continuous at
corner_detector
- 我用matlab写的一个corner detector, 效果比现在流行的harris，susan，CSS等效果要好。 Algorithm is derived from: X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Co
otsu.rar
- 本程序是利用最大类间方差算法求解自适应阈值，对图像进行分割,非动态阈值,This procedure is the use of maximum between-cluster variance adaptive thresholding algorithm for image segmentation, non-dynamic threshold
df
- 分布式环境的计算，课件的使用，以及各种资源-The research paper of “Segmentation methods of fruit image based on color difference” is mainly about four segmentation methods in fruit-harvesting robot vision, which respectively are dynamic threshold segmentation method, exte
GA_for_clustering
- Genetic algorithms (GAs) have recently been accepted as powerful approaches to solving optimization problems. It is also well-accepted that building block construction (schemata formation and conservation) has a positive influence on GA behavior.
Dynamic-Threshold
- 基于功率谱相减法的语音消噪，采用动态阈值法-Power spectrum subtraction based denoising of speech using dynamic threshold method
hundunpso
- 针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷 入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。 该方法考虑了图像中像素点灰度 邻域灰度均值对作为阈值对图像进行分割 利用混沌运 动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜 索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索 时间, 提高了收敛率
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- performance slightly decreases, in other words, matched filter detection scheme is sensitive to noise uncertainty at lower SNR values. By considering the dynamic threshold the performance is improved even in the case of noise uncertainty
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- shows the performance of matched filter detection by various parameters for a given , SNR=-15dB, N=150, noise uncertainty and dynamic threshold factor .From figure it is observed that with noise uncertainty the detection
otsu
- Otsu seeking dynamic threshold
paosang_v12
- 用MATLAB实现动态聚类或迭代自组织数据分析，ofdm系统仿真 含16qam调制 fft 加窗 加cp等模块，比较了软阈值，硬阈值及当今各种阈值计算方法。- Using MATLAB dynamic clustering or iterative self-organizing data analysis, ofdm system simulation including 16qam modulation fft windowing modules plus cp, Comparison of