Antenna switching apparatus based on spatial modulation
    72.
    发明授权
    Antenna switching apparatus based on spatial modulation 有权
    基于空间调制的天线切换装置

    公开(公告)号:US08942307B2

    公开(公告)日:2015-01-27

    申请号:US13912752

    申请日:2013-06-07

    CPC classification number: H04B7/0413 H01Q3/24 H01Q21/0006 H04B7/0604

    Abstract: An antenna switching apparatus based on spatial modulation includes a plurality of antennas; a control signal generator configured to generate a plurality of switching control signals; and a plurality of switches configured to switch on to apply a transmission signal to the respective antennas according to the respective switching control signals. Further, the antenna switching apparatus includes a delay analyzer configured to receive the transmission signal output from each of the plurality of switches to calculate delay information for synchronizing the switching control signals applied to the respective switches; and a delay adjuster configured to synchronize the switching control signals to apply the synchronized switching control signals to the respective switches according to the calculated delay information.

    Abstract translation: 基于空间调制的天线切换装置包括多个天线; 被配置为产生多个切换控制信号的控制信号发生器; 以及多个开关,其被配置为根据各个开关控制信号接通以将发送信号施加到各个天线。 此外,天线切换装置包括:延迟分析器,被配置为接收从多个开关中的每一个输出的发送信号,以计算用于使施加到各个开关的开关控制信号同步的延迟信息; 以及延迟调整器,被配置为使切换控制信号同步,以根据所计算的延迟信息将同步的切换控制信号施加到各个开关。

    Method of determining brain activity and electronic device performing the method

    公开(公告)号:US12178616B2

    公开(公告)日:2024-12-31

    申请号:US17974681

    申请日:2022-10-27

    Inventor: Seong Eun Kim

    Abstract: An electronic device according to an example embodiment includes a processor, and a memory operatively connected to the processor and including instructions executable by the processor, wherein when the instructions are executed, the processor is configured to collect an EEG signal measuring brain activity and an fNIRS signal measuring the brain activity, and output a result of determining a type of the brain activity from a trained neural network model using the EEG signal and the fNIRS signal, and the neural network model may be trained to, extract an EEG feature from the EEG signal, extract an fNIRS feature from the fNIRS signal, extract a fusion feature based on the EEG signal and the fNIRS signal, and output the result of determining the type of the brain activity based on the EEG feature and the fusion feature.

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