Offset stacked compressor amplifiers in a discrete digitizer system for noise reduction and increased resolution

    公开(公告)号:US10274520B2

    公开(公告)日:2019-04-30

    申请号:US14870357

    申请日:2015-09-30

    Abstract: A test and measurement instrument, including a splitter configured to split an input signal into two split input signals and output each split input signal onto a separate path and a combiner configured to receive and combine an output of each path to reconstruct the input signal. Each path includes an amplifier configured to receive the split input signal and to compress the split input signal with a sigmoid function, a digitizer configured to digitize an output of the amplifier; and at least one processor configured to apply an inverse sigmoid function on the output of the digitizer.

    Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing

    公开(公告)号:US09432042B2

    公开(公告)日:2016-08-30

    申请号:US14229307

    申请日:2014-03-28

    CPC classification number: H03M1/121 G01R13/0272 G01R23/14 H03M1/1215

    Abstract: A test and measurement instrument including a splitter configured to split an input signal having a particular bandwidth into a plurality of split signals, each split signal including substantially the entire bandwidth of the input signal; a plurality of harmonic mixers, each harmonic mixer configured to mix an associated split signal of the plurality of split signals with an associated harmonic signal to generate an associated mixed signal; and a plurality of digitizers, each digitizer configured to digitize a mixed signal of an associated harmonic mixer of the plurality of harmonic mixers. A first-order harmonic of at least one harmonic signal associated with the harmonic mixers is different from an effective sample rate of at least one of the digitizers.

    Harmonic time domain interleave to extend arbitrary waveform generator bandwidth and sample rate
    13.
    发明授权
    Harmonic time domain interleave to extend arbitrary waveform generator bandwidth and sample rate 有权
    谐波时域交织以扩展任意波形发生器带宽和采样率

    公开(公告)号:US09407280B1

    公开(公告)日:2016-08-02

    申请号:US14696857

    申请日:2015-04-27

    Inventor: John J. Pickerd

    CPC classification number: H03M1/662 H03M1/08 H03M1/1215

    Abstract: A harmonic time interleave (HTI) system, including a reference signal, a first summing component to produce a summed reference signal, a de-interleave block to receive an input signal and output a plurality of de-interleaved input signals, a plurality of digital-to-analog converters, each digital-to-analog converter configured to receive a corresponding one of a plurality of de-interleaved input signals and to output a corresponding analog signal, a plurality of mixing components, each mixing component configured to receive the summed reference signal and an analog signal from a corresponding of the plurality of digital-to-analog converters, and to output a corresponding mixed signal, and a second summing component configured to receive the mixed signal from each of the corresponding mixing components and to produce a substantially full-bandwidth analog signal representation of the input signal.

    Abstract translation: 包括参考信号的和谐时间交织(HTI)系统,产生相加的参考信号的第一求和分量,接收输入信号并输出​​多个解交织的输入信号的解交织块,多个数字 每个数/模转换器被配置为接收多个解交织的输入信号中的对应的一个,并且输出相应的模拟信号,多个混合分量,每个混合分量被配置为接收相加的 参考信号和来自多个数模转换器对应的模拟信号,并输出相应的混合信号,以及第二加法分量,被配置为从每个相应的混合分量接收混合信号并产生一个 基本上全带宽的模拟信号表示输入信号。

    ARBITRARY MULTIBAND OVERLAY MIXER APPARATUS AND METHOD FOR BANDWIDTH MULTIPLICATION
    14.
    发明申请
    ARBITRARY MULTIBAND OVERLAY MIXER APPARATUS AND METHOD FOR BANDWIDTH MULTIPLICATION 有权
    仲裁多重混合器装置和方法用于带宽乘法

    公开(公告)号:US20130237170A1

    公开(公告)日:2013-09-12

    申请号:US13869708

    申请日:2013-04-24

    CPC classification number: G01R13/0218 G01R13/0236 G01R13/0272 G01R19/2506

    Abstract: An apparatus and method for splitting a wide band input signal and overlaying multiple frequency bands on each path associated with one or more digitizers. All frequencies from the split signal on each path can be fed to a mixer. The local oscillator of each mixer receives a sum of signals, which can each be set to any arbitrary frequency, as long as an associated matrix determinant of coefficients is non-zero. Each oscillator signal is multiplied by a coefficient, which can represent phase and magnitude, prior to summing the oscillator signals together. Each mixer mixes a combined signal with the input, thereby generating a set of multiple overlaid frequency bands. The digitized signals are processed to substantially reconstruct the original input signal. Thus, the wide band input signal is digitized using multiple individual digitizers. In particular, a system can support two wide band signals using four digitizers of narrower bandwidth.

    Abstract translation: 一种用于分割宽带输入信号并在与一个或多个数字化仪相关联的每个路径上重叠多个频带的装置和方法。 来自每个路径上的分割信号的所有频率可以馈送到混频器。 每个混合器的本地振荡器接收信号总和,其可以被设置为任何任意频率,只要系数的相关联的矩阵行列式不为零。 在将振荡器信号相加在一起之前,每个振荡器信号乘以可表示相位和幅度的系数。 每个混合器将组合的信号与输入混合,从而生成一组多个重叠的频带。 处理数字化信号以基本上重建原始输入信号。 因此,使用多个单独的数字化仪将宽带输入信号数字化。 特别地,系统可以使用具有较窄带宽的四个数字化仪来支持两个宽带信号。

    INSTRUMENT AND MEASUREMENT TRANSLATOR USING MACHINE LEARNING

    公开(公告)号:US20250004015A1

    公开(公告)日:2025-01-02

    申请号:US18746902

    申请日:2024-06-18

    Abstract: A test and measurement system includes a first test and measurement instrument having an input to allow the test and measurement instrument to receive signals from one or more devices under test (DUT), and one or more digitizers to convert the signals from the one or more DUTs to digital waveforms, a machine learning network, and one or more processors to: perform one or more measurements of the digital waveforms, send the one or more measurements of the digital waveforms to the machine learning network as an input, use the machine learning network to translate the one or more measurements to measurements made by a reference instrument to produce one or more translated measurements, the reference instrument being more accurate than the first test and measurement instrument, and determine whether the DUT meets a performance requirement based upon the one or more translated measurements.

    USER INTERFACE FOR A TENSOR BUILDER TO CONSTRUCT IMAGES FOR INPUT TO MACHINE LEARNING

    公开(公告)号:US20240393918A1

    公开(公告)日:2024-11-28

    申请号:US18665258

    申请日:2024-05-15

    Abstract: A test and measurement instrument includes one or more ports to allow the test and measurement instrument to receive data from a device under test (DUT), a connection to a machine learning network, a display configured to display a user interface, one or more controls to allow the test and measurement instrument to receive inputs from a user, and one or more processors configured to execute code that causes the one or more processors to: render a menu on the display that displays different types of tensors, receive, from the one or more controls, a user selection that identifies a selected type of tensor, and build the selected type of tensor from the data from the DUT and send the selected type of tensor to the machine learning network. A method of providing a user interface is also disclosed.

    Cyclic loop image representation for waveform data

    公开(公告)号:US12092692B2

    公开(公告)日:2024-09-17

    申请号:US17345283

    申请日:2021-06-11

    Inventor: John J. Pickerd

    Abstract: A test and measurement instrument includes an input to receive a non-return-to-zero (NRZ) waveform signal from a device under test, a ramp generator to use the NRZ waveform signal to generate a ramp sweep signal, a gate to gate the ramp sweep signal and the NRZ waveform signal to produce gated X-axis and Y-axis data, and a display to display the gated X-axis and Y-axis data as a cyclic loop image. A method of generating a cyclic loop image includes receiving an input waveform, using the input waveform to generate a ramp sweep signal, gating the ramp sweep signal and the input waveform to produce gated X-axis and Y-axis data, and displaying the gated X-axis and Y-axis data as a cyclic loop image.

    AUTOMATED CHANNEL CHARACTERIZATION FOR MACHINE-LEARNING-BASED RIS-AIDED MIMO SYSTEMS

    公开(公告)号:US20240243779A1

    公开(公告)日:2024-07-18

    申请号:US18412151

    申请日:2024-01-12

    CPC classification number: H04B7/04013 H04B7/0413

    Abstract: A method of characterizing a communication channel includes receiving a first signal from a set of transmitters reflected along a reflected channel from each element of a reconfigurable intelligent surface (RIS) set at a nominal angle, receiving a second signal reflected in the reflected channel from each element of the RIS set at an adjusted angle, using the first and second signals to determine a transfer function for a combined channel comprised of a reflected channel and a direct channel, and using the transfer function as an input to a machine learning network to determine optimized settings for the elements of the RIS. A communications system includes a set of transmitters, a reconfigurable intelligent surface (RIS), one or more receivers positioned to receive signals reflected by the RIS from the set of transmitters, and a machine learning system configured to produce optimized angles for elements of the RIS.

    MACHINE LEARNING MODEL DISTRIBUTION ARCHITECTURE

    公开(公告)号:US20240184637A1

    公开(公告)日:2024-06-06

    申请号:US18523556

    申请日:2023-11-29

    CPC classification number: G06F9/5077 G06F11/362

    Abstract: A machine learning management system includes a repository having one or more partitions, the one or more partitions being separate from others of the partitions, a communications interface, and one or more processors configured to execute code to: receive a selected model and associated training data for the selected model through the communications interface from a customer; store the selected model and the associated training data in a partition dedicated to the customer; and manage the one or more partitions to ensure that the customer can only access the customer's partition. A method includes receiving a selected model and associated training data for the selected model from a customer, storing the selected model and the associated training data in a partition dedicated to the customer in a repository, and managing the one or more partitions to ensure that the customer can only access the partition dedicated to the customer.

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