METHOD AND DEVICES FOR NON-INTRUSIVE POWER MONITORING
    41.
    发明申请
    METHOD AND DEVICES FOR NON-INTRUSIVE POWER MONITORING 有权
    用于非侵入式电力监测的方法和装置

    公开(公告)号:US20140333281A1

    公开(公告)日:2014-11-13

    申请号:US13890731

    申请日:2013-05-09

    Inventor: Qing LI

    Abstract: A method and device are disclosed for estimating a power demand level of an active circuit on a power supply line. A ripple amplitude and a ripple frequency associated with operation of the active circuit may be monitored on the power supply line. The ripple amplitude and ripple frequency may be compared with corresponding references. The ripple amplitude and ripple frequency may be associated with an estimated power demand level of the active circuit on the power supply line based on the comparison. A ripple generator generates a controlled ripple on the power supply line for calibration.

    Abstract translation: 公开了一种用于估计电源线上的有源电路的功率需求水平的方法和装置。 可以在电源线上监视与有源电路的操作相关联的纹波幅度和纹波频率。 纹波幅度和纹波频率可以与相应的参考值进行比较。 基于比较,纹波幅度和纹波频率可以与电源线上的有源电路的估计功率需求水平相关联。 波纹发生器在电源线上产生受控纹波进行校准。

    SIDELINK LISTEN-BEFORE-TALK SENSING

    公开(公告)号:US20250133589A1

    公开(公告)日:2025-04-24

    申请号:US18490554

    申请日:2023-10-19

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. Some aspects more specifically relate to consistent listen-before-talk (LBT) failure recovery for sidelink communications. In some aspects, a medium access control (MAC) layer may transmit, and a physical (PHY) layer may receive, an indication to perform LBT sensing for one or more resource block sets associated with a consistent LBT failure. The indication to perform LBT sensing may be an indication to perform LBT sensing for sidelink communications without transmitting data. The PHY layer may transmit, and the MAC layer may receive, a result of the LBT sensing. In some aspects, the indication to perform the LBT sensing may be an indication to perform Type 1 LBT sensing or an indication to perform Type 2 LBT sensing, and/or may indicate a quantity of LBT sensing operations to be performed.

    EFFICIENT COMMUNICATION AND COMPUTATION FOR SPLIT-TRAINING OF MACHINE LEARNING MODELS

    公开(公告)号:US20250086450A1

    公开(公告)日:2025-03-13

    申请号:US18463108

    申请日:2023-09-07

    Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning training process. Input data for a first portion of a neural network is accessed, and output data is generated based on processing the input data using the first portion of the neural network. At a first point in time, the output data is transmitted to a second computing system for the second computing system to update one or more parameters of a second portion of the neural network based on the output data. It is determined, at a second point in time subsequent to the first point in time, that one or more communication criteria are not satisfied. In response to the determining, reduced communication training of the neural network is performed, the performing comprising reducing an amount of data transmitted for one or more rounds of training.

    TECHNIQUES FOR MANAGING WIRELESS ANALYTICS IN SIDELINK COMMUNICATIONS

    公开(公告)号:US20240373196A1

    公开(公告)日:2024-11-07

    申请号:US18777216

    申请日:2024-07-18

    Abstract: Techniques for wireless communications are described. A first device may receive first control signaling that may indicate a second device in a wireless communications system. The first device may then identify, based on the received first control signaling, a set of devices for tracking the second device in the wireless communications system. In some examples, the first device may then transmit second control signaling to the identified set of devices for tracking the second device in the wireless communications system. The first device may then receive, based on the transmitted second control signaling, coordination information from the set of devices. The received coordination information may be associated with the second device. The coordination information collected by the set of devices may be used to predict changes in an environment surrounding the second device. By predicting dynamic changes in the environment, disruptions in wireless communication may be prevented.

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