公开(公告)号：US08407168B2

公开(公告)日：2013-03-26

申请号：US12828617

申请日：2010-07-01

申请人： Cheng-Fa Tsai ,  Yu-Chun Lin

发明人： Cheng-Fa Tsai ,  Yu-Chun Lin

IPC分类号： G06F15/18 ,  G06F13/12

CPC分类号： G06N3/08

摘要： A codebook generating method includes a dividing and transforming step dividing an original image into original blocks and transforming the original blocks into original vectors; a dividing step grouping the original vectors to obtain centroids; a first layer neuron training step selecting a portion of the centroids as first-level neurons; a grouping step assigning each of the original vectors to a closest first-level neuron so as to obtain groups; a second layer neuron assigning step assigning a number of second-level neurons in each of the groups, and selecting a portion of the original vectors in each of the groups as the second-level neurons; and a second layer neuron training step defining the original vectors in each of the groups as samples, training the second-level neurons in each of the groups to obtain final neurons, and storing vectors corresponding to the final neurons in a codebook.

摘要翻译： 码本生成方法包括将原始图像分割成原始块并将原始块变换成原始向量的分割和变换步骤; 将原始矢量分组以获得质心的分割步骤; 选择一部分质心作为一级神经元的第一层神经元训练步骤; 分配步骤，将每个原始矢量分配给最接近的一级神经元，以便获得组; 第二层神经元分配步骤，在每个组中分配多个第二级神经元，并且将每组中的原始向量的一部分选择为第二级神经元; 以及第二层神经元训练步骤，将每组中的原始矢量定义为样本，训练每组中的第二级神经元以获得最终神经元，并将对应于最终神经元的载体存储在码本中。

公开(公告)号：US20120296906A1

公开(公告)日：2012-11-22

申请号：US13468721

申请日：2012-05-10

申请人： Cheng-Fa TSAI ,  Chun-Hao CHANG

发明人： Cheng-Fa TSAI ,  Chun-Hao CHANG

IPC分类号： G06F17/30

CPC分类号： G06F17/30598

摘要： A grid-based data clustering method performed by a computer system includes a setup step, a dividing step, a categorizing step and an expanding/clustering step. The setup step sets a grid quantity and a threshold value. The dividing step divides a space containing a data set having a plurality of data points into a two-dimensional matrix. The matrix has a plurality of grids G(i,j) comprising a plurality of target sequences and a plurality of non-target sequences interlaced with the plurality of target sequences. The indices “i” and “j” of each grid G(i,j) represents the coordinate thereof. The categorizing step determines whether each of the grids is valid based on the threshold value. The expanding/clustering step respectively retrieves each of the grids of the target sequences, performs an expansion operation on each of the grids retrieved and clusters the plurality grids G(i,j).

摘要翻译： 由计算机系统执行的基于网格的数据聚类方法包括设置步骤，分割步骤，分类步骤和扩展/聚类步骤。 设置步骤设置网格数量和阈值。 分割步骤将包含具有多个数据点的数据集的空间划分成二维矩阵。 矩阵具有包含与多个目标序列隔行的多个目标序列和多个非目标序列的多个网格G（i，j）。 每个网格G（i，j）的索引i和j表示其坐标。 分类步骤基于阈值确定每个网格是否有效。 扩展/聚集步骤分别检索目标序列的每个网格，对所检索的每个网格执行扩展操作，并聚集多个网格G（i，j）。

公开(公告)号：US08171025B2

公开(公告)日：2012-05-01

申请号：US12683202

申请日：2010-01-06

申请人： Cheng-Fa Tsai ,  Chien-Tsung Wu

发明人： Cheng-Fa Tsai ,  Chien-Tsung Wu

IPC分类号： G06F17/30

CPC分类号： G06F17/30705 ,  G06K9/622 ,  G06K9/6276

摘要： A density-based data clustering method, comprising a parameter-setting step for setting a scanning radius and a minimum threshold value, a dividing step for dividing a space of a plurality of data points according to the scanning radius, a data-retrieving step for retrieving one data point out of the plurality of data points as a core data point, a searching step for calculating a distance between the core data point and each of the query points, a grouping determination step for determining whether a number of the neighboring points is smaller than the minimum threshold value.

摘要翻译： 一种基于密度的数据聚类方法，包括用于设置扫描半径和最小阈值的参数设置步骤，用于根据扫描半径分割多个数据点的空间的划分步骤，用于 从所述多个数据点中取出一个数据点作为核心数据点;计算所述核心数据点与每个所述查询点之间的距离的搜索步骤;分组确定步骤，用于确定所述相邻点的数量是否为 小于最小阈值。

公开(公告)号：US08037533B2

公开(公告)日：2011-10-11

申请号：US12021342

申请日：2008-01-29

申请人： Cheng-Fa Tsai ,  Chia-Chen Yen

发明人： Cheng-Fa Tsai ,  Chia-Chen Yen

IPC分类号： G06F11/00 ,  G06F17/00

CPC分类号： H04L63/1425 ,  G06F21/55

摘要： A detecting method for network intrusion includes: selecting a plurality of features contained within plural statistical data by a data-transforming module; normalizing a plurality of feature values of the selected features into the same scale to obtain a plurality of normalized feature data; creating at least one feature model by a data clustering technique incorporated with density-based and grid-based algorithms through a model-creating module; evaluating the at least one feature model through a model-identifying module to select a detecting model; and detecting whether a new packet datum belongs to an intrusion instance or not by a detecting module.

摘要翻译： 一种用于网络入侵的检测方法包括：通过数据转换模块选择多个统计数据中包含的多个特征; 将所选择的特征的多个特征值归一化为相同的比例以获得多个归一化特征数据; 通过模型创建模块通过结合基于密度和基于网格的算法的数据聚类技术创建至少一个特征模型; 通过模型识别模块来评估所述至少一个特征模型以选择检测模型; 以及检测模块检测新的分组数据是否属于入侵实例。

公开(公告)号：US20080154942A1

公开(公告)日：2008-06-26

申请号：US11958461

申请日：2007-12-18

申请人： Cheng-Fa Tsai ,  Chia-Chen Yen

发明人： Cheng-Fa Tsai ,  Chia-Chen Yen

IPC分类号： G06F17/30

CPC分类号： G06F17/30979 ,  G06F17/30705

摘要： A method for grid-based data clustering comprises: creating a feature space having a plurality of cubes by a computer and showing the feature space by an interface of the computer, disposing a plurality of data stored in a database into the cubes, and then defining a plurality of the cubes as populated cubes; identifying whether the data within each of the populated cubes being evenly distributed or not to define each populated cube as a major cube or minor cube; combining border data of the minor cubes with the data in the major cubes; and designating all the data combined with each other as in the same cluster and recursively processing the above procedures to cluster all the data stored in the database.

摘要翻译： 一种用于基于网格的数据聚类的方法包括：通过计算机创建具有多个立方体的特征空间，并通过计算机的接口显示特征空间，将存储在数据库中的多个数据放置到立方体中，然后定义 多个立方体作为填充的立方体; 识别每个填充的多维数据集中的数据是否均匀分布，以将每个填充的多维数据集定义为主要立方体或次立方体; 将次立方体的边界数据与主立方体中的数据组合; 并指定在同一个集群中相互组合的所有数据，并递归地处理上述过程来集群存储在数据库中的所有数据。

公开(公告)号：US08661040B2

公开(公告)日：2014-02-25

申请号：US13468721

申请日：2012-05-10

申请人： Cheng-Fa Tsai ,  Chun-Hao Chang

发明人： Cheng-Fa Tsai ,  Chun-Hao Chang

IPC分类号： G06N5/00 ,  G06F17/30

CPC分类号： G06F17/30598

摘要： A grid-based data clustering method performed by a computer system includes a setup step, a dividing step, a categorizing step and an expanding/clustering step. The setup step sets a grid quantity and a threshold value. The dividing step divides a space containing a data set having a plurality of data points into a two-dimensional matrix. The matrix has a plurality of grids G(i,j) comprising a plurality of target sequences and a plurality of non-target sequences interlaced with the plurality of target sequences. The indices “i” and “j” of each grid G(i,j) represents the coordinate thereof. The categorizing step determines whether each of the grids is valid based on the threshold value. The expanding/clustering step respectively retrieves each of the grids of the target sequences, performs an expansion operation on each of the grids retrieved and clusters the plurality grids G(i,j).

摘要翻译： 由计算机系统执行的基于网格的数据聚类方法包括设置步骤，分割步骤，分类步骤和扩展/聚类步骤。 设置步骤设置网格数量和阈值。 分割步骤将包含具有多个数据点的数据集的空间划分成二维矩阵。 矩阵具有包含与多个目标序列隔行的多个目标序列和多个非目标序列的多个网格G（i，j）。 每个网格G（i，j）的索引“i”和“j”表示其坐标。 分类步骤基于阈值确定每个网格是否有效。 扩展/聚集步骤分别检索目标序列的每个网格，对所检索的每个网格执行扩展操作，并聚集多个网格G（i，j）。

公开(公告)号：US08429166B2

公开(公告)日：2013-04-23

申请号：US13462460

申请日：2012-05-02

申请人： Cheng-Fa Tsai ,  Tang-Wei Huang

发明人： Cheng-Fa Tsai ,  Tang-Wei Huang

IPC分类号： G06F7/00 ,  G06F17/30 ,  G06F15/16

CPC分类号： G06F17/30598

摘要： A density-based data clustering method executed by a computer system is disclosed. The method includes a setup step, a clustering step, an expansion step and a termination step. The setup step sets a radius and a threshold value. The clustering step defines a single cluster on a plurality of data points of a data set, and provides and adds a plurality of first boundary marks to a seed list as seeds. The expansion step expands the cluster from each seed of the seed list, and provides and adds at least one second boundary mark to the seed list as seeds. The termination step determines whether each of the data points is clustered, wherein the clustering step is re-performed if the determination is negative.

摘要翻译： 公开了一种由计算机系统执行的基于密度的数据聚类方法。 该方法包括设置步骤，聚类步骤，扩展步骤和终止步骤。 设置步骤设置半径和阈值。 聚类步骤在数据集合的多个数据点上定义单个簇，并且将种子列表中的多个第一边界标记提供并添加到种子列表中。 扩展步骤从种子列表的每个种子扩展集群，并为种子提供并添加至少一个第二个边界标记到种子列表。 终止步骤确定每个数据点是否是聚类的，其中如果确定为负，则重新执行聚类步骤。

公开(公告)号：US08166035B2

公开(公告)日：2012-04-24

申请号：US12652979

申请日：2010-01-06

申请人： Cheng-Fa Tsai ,  Chien-Sheng Chiu

发明人： Cheng-Fa Tsai ,  Chien-Sheng Chiu

IPC分类号： G06F17/30

CPC分类号： G06F17/30705 ,  G06K9/6218

摘要： A grid-based data clustering method comprises: a parameter setting step, a partition step, a searching step, a seed-classifying step, an extension step, and a termination step. Through the above-mentioned steps, data in a data set are disposed in a plurality of grids, and the grids are classified into dense grids and uncrowded grids for a cluster to extend from one of the dense grid to gradually combine data in other dense grids nearby. Consequently, convenience in parameter setting, efficiency and accuracy in data clustering, and performance in noise filtering are achieved.

摘要翻译： 基于网格的数据聚类方法包括：参数设置步骤，分区步骤，搜索步骤，种子分类步骤，扩展步骤和终止步骤。 通过上述步骤，将数据集中的数据设置在多个网格中，并且网格被分类为密集网格和未填充网格，用于从一个密集网格延伸到逐渐组合其他密集网格中的数据 附近。 因此，实现了参数设置的方便性，数据聚类的效率和精度以及噪声滤波中的性能。

公开(公告)号：US20110040758A1

公开(公告)日：2011-02-17

申请号：US12652979

申请日：2010-01-06

申请人： Cheng-Fa TSAI ,  Chien-Sheng Chiu

发明人： Cheng-Fa TSAI ,  Chien-Sheng Chiu

IPC分类号： G06F17/30

CPC分类号： G06F17/30705 ,  G06K9/6218

摘要： A grid-based data clustering method comprises: a parameter setting step, a partition step, a searching step, a seed-classifying step, an extension step, and a termination step. Through the above-mentioned steps, data in a data set are disposed in a plurality of grids, and the grids are classified into dense grids and uncrowded grids for a cluster to extend from one of the dense grid to gradually combine data in other dense grids nearby. Consequently, convenience in parameter setting, efficiency and accuracy in data clustering, and performance in noise filtering are achieved.

摘要翻译： 基于网格的数据聚类方法包括：参数设置步骤，分区步骤，搜索步骤，种子分类步骤，扩展步骤和终止步骤。 通过上述步骤，将数据集中的数据设置在多个网格中，并且网格被分类为密集网格和未填充网格，用于从一个密集网格延伸到逐渐组合其他密集网格中的数据 附近。 因此，实现了参数设置的方便性，数据聚类的效率和精度以及噪声滤波中的性能。

公开(公告)号：US20090046630A1

公开(公告)日：2009-02-19

申请号：US12186583

申请日：2008-08-06

申请人： Cheng-Fa Tsai ,  Shih-Yuan Chao

发明人： Cheng-Fa Tsai ,  Shih-Yuan Chao

IPC分类号： H04Q7/00

CPC分类号： H04W84/18 ,  H04W28/08 ,  H04W52/0219

摘要： A data-transmitting method for wireless sensor network comprises: constructing a wireless sensor network having a plurality of nodes for information sensing and a sink for quest raising and data collecting; clustering the nodes to form a plurality of groups, with one of the nodes in each group being identified as a kernel; identifying one of all the nodes as a summit dissemination node and the kernels in all the groups as first level dissemination nodes; and transmitting data between the quest-raising sink and one of the first level dissemination nodes or summit dissemination node to collect information sensed by a source that is one of the nodes.

摘要翻译： 一种用于无线传感器网络的数据传输方法，包括：构建具有用于信息感测的多个节点的无线传感器网络和用于任务提升和数据采集的接收器; 将节点聚类以形成多个组，每个组中的一个节点被识别为内核; 将所有节点中的一个标识为峰顶传播节点，将所有组中的内核识别为第一级传播节点; 以及在所述寻求接收器和所述第一级传播节点或所述顶点传播节点之一之间传送数据，以收集由作为所述节点之一的源所感测的信息。