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    • 21. 发明申请
    • Method and Apparatus for Acoustic Area Monitoring by Exploiting Ultra Large Scale Arrays of Microphones
    • 利用超大型麦克风阵列进行声区监测的方法与装置
    • US20140098964A1
    • 2014-04-10
    • US13644432
    • 2012-10-04
    • Justinian RoscaHeiko ClaussenRadu Victor Balan
    • Justinian RoscaHeiko ClaussenRadu Victor Balan
    • H04R29/00
    • H04R1/406H04R3/005H04R2430/03H04R2430/23
    • Systems and methods are provided to create an acoustic map of a space containing multiple acoustic sources. Source localization and separation takes place by sampling an ultra large microphone array containing over 1020 microphones. The space is divided into a plurality of masks, wherein each masks represents a pass region and a complementary rejection region. Each mask is associated with a subset of microphones and beamforming filters that maximize a gain for signals coming from the pass region of the mask and minimizes the gain for signals from the complementary region according to an optimization criterion. The optimization criterion may be a minimization of a performance function for the beamforming filters. The performance function is preferably a convex function. A processor provides a scan applying the plurality of masks to locate a target source. Processor based systems to perform the optimization are also provided.
    • 提供系统和方法来创建包含多个声源的空间的声学图。 源定位和分离是通过对包含超过1020个麦克风的超大麦克风阵列进行采样而进行的。 该空间被分成多个掩模,其中每个掩模表示通过区域和互补的拒绝区域。 每个掩模与麦克风和波束形成滤波器的子集相关联,其使来自掩模的通过区域的信号的增益最大化,并且根据优化标准使来自互补区域的信号的增益最小化。 优化标准可以是波束形成滤波器的性能函数的最小化。 性能函数优选为凸函数。 处理器提供应用多个掩模以定位目标源的扫描。 还提供了基于处理器的系统来执行优化。
    • 22. 发明申请
    • Method for Congestion Detection in Packet Transmission Networks
    • 分组传输网络拥塞检测方法
    • US20110134751A1
    • 2011-06-09
    • US13026364
    • 2011-02-14
    • Radu Victor BalanChih-Wei HuangJustinian RoscaOctavian Sarca
    • Radu Victor BalanChih-Wei HuangJustinian RoscaOctavian Sarca
    • H04L12/26
    • H04L47/10H04L43/00H04L43/0847H04L43/0888H04L43/0894H04L47/11H04L47/14H04L47/28H04W28/10
    • A method for measuring degree of packet congestion on a channel of a packet communication network. The method includes: during a training mode, generating an mathematical relationship between the degree of packet congestion on the channel and a plurality of measurable features of the network over a plurality of network conditions; and, during a subsequent normal operating mode, periodically measuring the plurality of measurable features and applying the generated mathematical relationship to such periodically measured plurality of measurable features to determine actual degree of congestion on the channel; and comparing the actual degree of congestion on the channel with a predetermined channel congestion threshold level. The degree of packet congestion on the channel is saturation level. The measurable features include: lime delay between transmission starts and terminations of the previously transmitted packet; the fraction of time the channel is busy; and. average number of packet transmission retries.
    • 一种用于测量分组通信网络的信道上的分组拥塞程度的方法。 该方法包括:在训练模式期间,在多个网络条件下,在信道上的分组拥塞程度与网络的多个可测量特征之间产生数学关系; 并且在随后的正常操作模式期间,周期性地测量所述多个可测量特征并将所生成的数学关系应用于所述周期性测量的多个可测量特征以确定所述信道上的实际拥塞程度; 以及将所述信道上的实际拥塞程度与预定信道拥塞阈值级别进行比较。 信道上的分组拥塞程度是饱和度。 可测量的特征包括:传输开始之间的灰色延迟和先前发送的分组的终止; 频道繁忙时间的一小部分; 和。 平均分组传输重试次数。
    • 25. 发明授权
    • Online blind source separation
    • 在线盲源分离
    • US06954494B2
    • 2005-10-11
    • US10027964
    • 2001-10-25
    • Scott RickardRadu Victor BalanJustinian Rosca
    • Scott RickardRadu Victor BalanJustinian Rosca
    • G06K9/62H03H21/00H03H7/30H03H7/40H03K5/159
    • H03H21/0012G06K9/624H03H2021/0034
    • A method for blind source separation of sources detects the sources using sensors to obtain representative data. The data is then represented by two mixtures having estimates of amplitude and delay mixing parameters. The estimates are updated, including: calculating error measures, each indicating a closeness of the estimates for a given source to a given time-frequency point in the mixtures; and revising the estimates, based on the error measures. The mixtures are filtered to obtain estimates of the sources, including: selecting one error measure having a smallest value in relation to any other error measures, for each time-frequency point in the mixtures; and leaving unaltered any time-frequency points for which a given error measure has the smallest value, while setting to zero any other time-frequency points for which the given error measure does not have the smallest value, for each error measure. The estimates of the sources are output.
    • 用于盲源分离源的方法使用传感器来检测源以获得代表性数据。 数据由具有振幅和延迟混合参数估计的两个混合物表示。 估计值已更新,包括:计算误差测量值,每个误差测量值表示给定源的估计值与混合物中给定时间点的接近程度; 并根据错误措施修改估计数。 过滤混合物以获得源的估计,包括:为混合物中的每个时间点选择与任何其它误差测量相关的最小值的一个误差测量; 并且对于每个误差测量,将给定误差测量具有最小值的任何时间频率点保持不变,同时将给定误差测量值不具有最小值的任何其他时间点设置为零。 来源的估计是输出。