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    • 7. 发明授权
    • Active sonar system and active sonar method using fuzzy logic
    • 主动声纳系统和主动声纳法采用模糊逻辑
    • US08320216B2
    • 2012-11-27
    • US12628246
    • 2009-12-01
    • Qin Jiang
    • Qin Jiang
    • G01S15/00
    • G01S15/42G01S7/53G01S7/534G01S7/539
    • A computer-implemented method of sonar processing includes identifying, with a processor, a detection having a detection probability value, the detection in a selected beam, wherein the detection is associated with a detection range cell having detection range cell data. The method also includes comparing, with the processor, the detection range cell data with range cell data from a corresponding range cell from at least one overlapping beam overlapping the selected beam. The method also includes updating, with the processor, the detection probability value based upon the comparing. A sonar system uses the above-described method. A computer readable storage medium has instructions thereon to achieve the above-described method.
    • 计算机实现的声纳处理方法包括用处理器识别具有检测概率值的检测,所述检测与所选择的波束中的检测相关联,其中所述检测与具有检测范围单元数据的检测范围单元相关联。 该方法还包括将检测范围单元数据与来自与所选择的波束重叠的至少一个重叠波束的对应范围单元的距离单元数据进行比较。 该方法还包括基于该比较与处理器更新检测概率值。 声纳系统使用上述方法。 计算机可读存储介质在其上具有实现上述方法的指令。
    • 8. 发明申请
    • ACTIVE SONAR SYSTEM AND ACTIVE SONAR METHOD USING FUZZY LOGIC
    • 使用FUZZY LOGIC的主动声纳系统和主动声纳方法
    • US20110128819A1
    • 2011-06-02
    • US12628246
    • 2009-12-01
    • Qin Jiang
    • Qin Jiang
    • G01S15/00
    • G01S15/42G01S7/53G01S7/534G01S7/539
    • A computer-implemented method of sonar processing includes identifying, with a processor, a detection having a detection probability value, the detection in a selected beam, wherein the detection is associated with a detection range cell having detection range cell data. The method also includes comparing, with the processor, the detection range cell data with range cell data from a corresponding range cell from at least one overlapping beam overlapping the selected beam. The method also includes updating, with the processor, the detection probability value based upon the comparing. A sonar system uses the above-described method. A computer readable storage medium has instructions thereon to achieve the above-described method.
    • 计算机实现的声纳处理方法包括用处理器识别具有检测概率值的检测,所述检测与所选择的波束中的检测相关联,其中所述检测与具有检测范围单元数据的检测范围单元相关联。 该方法还包括将检测范围单元数据与来自与所选择的波束重叠的至少一个重叠波束的对应范围单元的距离单元数据进行比较。 该方法还包括基于该比较与处理器更新检测概率值。 声纳系统使用上述方法。 计算机可读存储介质在其上具有实现上述方法的指令。
    • 9. 发明申请
    • STACKED THERMOCOUPLE STRUCTURE AND SENSING DEVICES FORMED THEREWITH
    • 堆积的热电偶结构和传感装置
    • US20050016576A1
    • 2005-01-27
    • US10710250
    • 2004-06-29
    • Qin JiangHan LeeJames LogsdonDan ChilcottDavid LambertShih-Chia Chang
    • Qin JiangHan LeeJames LogsdonDan ChilcottDavid LambertShih-Chia Chang
    • G01K7/02H01L35/00H01L35/28H01L35/30H01L37/00
    • G01K7/021
    • A thermocouple structure capable of providing a more compact thermopile-based thermal sensor. The thermocouple structure has a stacked configuration that includes a plurality of first conductors on a surface, a dielectric layer on each of the first conductors, and a plurality of second conductors on the dielectric layer and formed of a different material than the first conductors. Each first conductor has first and second ends, and each second conductor has a first end overlying and contacting the first end of one of the first conductors, and a second end overlying but separated from the second end of the first conductor by the dielectric layer. A plurality of third conductors electrically interconnect one of the second ends of the second conductors with one of the second ends of the first conductors. Each third conductors is thicker than the second conductors to promote the robustness of the connection.
    • 能够提供更紧凑的基于热电堆的热传感器的热电偶结构。 热电偶结构具有层叠结构,其包括表面上的多个第一导体,每个第一导体上的电介质层和介电层上的多个第二导体,并且由不同于第一导体的材料形成。 每个第一导体具有第一端和第二端,并且每个第二导体具有覆盖并接触第一导体中的一个的第一端的第一端,以及通过介电层覆盖但与第一导体的第二端分离的第二端。 多个第三导体将第二导体的第二端中的一个与第一导体的第二端之一电互连。 每个第三导体比第二导体厚,以促进连接的鲁棒性。
    • 10. 发明授权
    • System for automatic data clustering utilizing bio-inspired computing models
    • 使用生物启发计算模型的自动数据聚类系统
    • US09009156B1
    • 2015-04-14
    • US12590574
    • 2009-11-10
    • Qin JiangYang Chen
    • Qin JiangYang Chen
    • G06F17/30
    • G06F15/1735G06N3/0409G06N3/0418G06N3/0436
    • Described is a system for automatic data clustering which utilizes bio-inspired computing models. The system performs operations of mapping a set of input data into a feature space using a bio-inspired computing model. A number of clusters inside the set of input data is then determined by finding an optimal vigilance parameter using a bio-inspired computing model. Finally, the set of input data is clustered based on the determined number of clusters. The input data is mapped with a Freeman's KIII network, such that each data point is mapped into a KIII network response. Furthermore, the number of clusters is determined using the fuzzy adaptive resonance theory (ART), and the data is clustered using the fuzzy c-means method. Clustering quality measures are used to compute an objective function to evaluate the quality of clustering.
    • 描述了一种利用生物启发计算模型的自动数据聚类系统。 系统执行使用生物启发的计算模型将一组输入数据映射到特征空间的操作。 然后通过使用生物启发的计算模型找到最佳警戒参数来确定输入数据集合内的多个群集。 最后,基于所确定的群集数量对该组输入数据进行聚类。 输入数据用Freeman的KIII网络映射,使得每个数据点被映射到KIII网络响应。 此外,使用模糊自适应共振理论(ART)确定簇的数量,并且使用模糊c-means方法对数据进行聚类。 聚类质量测度用于计算目标函数,以评估聚类质量。