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    WIRELESS DEVICES AND SYSTEMS INCLUDING EXAMPLES OF CROSS CORRELATING WIRELESS TRANSMISSIONS
    2.
    发明公开
    WIRELESS DEVICES AND SYSTEMS INCLUDING EXAMPLES OF CROSS CORRELATING WIRELESS TRANSMISSIONS 审中-公开

    公开(公告)号：US20240178987A1

    公开(公告)日：2024-05-30

    申请号：US18436965

    申请日：2024-02-08

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Tamara Schmitz ,  Jeremy Chritz ,  Jaime Cummins

    IPC: H04L7/04 ,  H04L27/00 ,  H04L27/26

    CPC classification number: H04L7/042 ,  H04L27/0006 ,  H04L27/2647 ,  H04L27/2663 ,  H04L27/2678

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of cross correlation including symbols indicative of radio frequency (RF) energy. An electronic device including a statistic calculator may be configured to calculate a statistic including the cross-correlation of the symbols. The electronic device may include a comparator configured to provide a signal indicative of a presence or absence of a wireless communication signal in the particular portion of the wireless spectrum based on a comparison of the statistic with a threshold. A decoder/precoder may be configured to receive the signal indicative of the presence or absence of the wireless communication signal and to decode the symbols responsive to a signal indicative of the presence of the wireless communication signal. Examples of systems and methods described herein may facilitate the processing of data for wireless communications in a power-efficient and time-efficient manner.

    Neuron calculator for artificial neural networks
    4.
    发明授权
    Neuron calculator for artificial neural networks 有权

    公开(公告)号：US11870513B2

    公开(公告)日：2024-01-09

    申请号：US17362672

    申请日：2021-06-29

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Jaime Cummins ,  Tamara Schmitz ,  Jeremy Chritz

    IPC: G06K9/00 ,  H04B7/0413 ,  G06N3/08 ,  G06N3/04

    CPC classification number: H04B7/0413 ,  G06N3/04 ,  G06N3/08

    Abstract: Examples described herein include systems and methods, including wireless devices and systems with neuron calculators that may perform one or more functionalities of a wireless transceiver. The neuron calculator calculates output signals that may be implemented, for example, using accumulation units that sum the multiplicative processing results of ordered sets from ordered neurons with connection weights for each connection between an ordered neuron and outputs of the neuron calculator. The ordered sets may be a combination of some input signals, with the number of signals determined by an order of the neuron. Accordingly, a kth-order neuron may include an ordered set comprising product values of k input signals, where the input signals are selected from a set of k-combinations with repetition. As an example in a wireless transceiver, the neuron calculator may perform channel estimation as a channel estimation processing component of the receiver portion of a wireless transceiver.

    MEASURING CHANGE IN A CHANNEL CHARACTERISTIC TO DETECT MEMORY DEVICE ATTACK
    5.
    发明申请
    MEASURING CHANGE IN A CHANNEL CHARACTERISTIC TO DETECT MEMORY DEVICE ATTACK 有权

    公开(公告)号：US20230063890A1

    公开(公告)日：2023-03-02

    申请号：US17459543

    申请日：2021-08-27

    Applicant: Micron Technology, Inc.

    Inventor： Aaron Boehm ,  Jeremy Chritz ,  Tamara Schmitz ,  David Hulton ,  Max Vohra

    IPC: G06F21/55 ,  G06F3/06

    Abstract: Methods, systems, and devices for measuring change in a channel characteristic to detect a memory device attack are described. A system, such as a vehicle system, may include a host device coupled with a memory device. The host device may transmit a first signal to the memory device and may receive, from the memory device, a second signal as feedback based on the first signal. The host device may determine a channel characteristic, such as a channel impedance measurement, based on the second signal received from the memory device. If the determined channel characteristic fails to satisfy a threshold (e.g., if the measured channel impedance fails to satisfy a reference value within a tolerance range), the host device may detect a potential attack on the memory device and may take corrective action, such as disabling one or more features of the memory device.

    Image processor formed in an array of memory cells
    6.
    发明授权
    Image processor formed in an array of memory cells 有权

    公开(公告)号：US11445157B2

    公开(公告)日：2022-09-13

    申请号：US17150828

    申请日：2021-01-15

    Applicant: Micron Technology, Inc.

    Inventor： Fa-Long Luo ,  Jaime C. Cummins ,  Tamara Schmitz

    IPC: H04N9/67 ,  H04N1/60 ,  G06F17/16 ,  H04N9/73

    Abstract: Apparatuses, systems, and methods related to an image processor formed in an array of memory cells are described. An image processor as described herein is configured to reduce complexity and power consumption and/or increase data access bandwidth by performing image processing in the array of memory cells relative to image processing by a host processor external to the memory array. For instance, one apparatus described herein includes sensor circuitry configured to provide an input vector, as a plurality of bits that corresponds to a plurality of color components for an image pixel, and an image processor formed in an array of memory cells. The image processor is coupled to the sensor circuitry to receive the plurality of bits of the input vector. The image processor is configured to perform a color correction operation in the array by performing matrix multiplication on the input vector and a parameter matrix to determine an output vector that is color corrected.

    Self interference noise cancellation to support multiple frequency bands
    7.
    发明授权
    Self interference noise cancellation to support multiple frequency bands 有权

    公开(公告)号：US11206050B2

    公开(公告)日：2021-12-21

    申请号：US15890275

    申请日：2018-02-06

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Jaime Cummins ,  Tamara Schmitz ,  Jeremy Chritz

    IPC: H04W72/08 ,  H04B1/04 ,  H04L5/14 ,  H04B1/525

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator that compensates for the self-interference noise generated by power amplifiers at harmonic frequencies of a respective wireless receiver. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate the adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is receivable by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same or different frequency band as the wireless receiver is receiving.

    Autocorrelation and memory allocation for wireless communication
    8.
    发明授权
    Autocorrelation and memory allocation for wireless communication 有权

    公开(公告)号：US11201646B2

    公开(公告)日：2021-12-14

    申请号：US16844178

    申请日：2020-04-09

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Tamara Schmitz ,  Jeremy Chritz ,  Jaime Cummins

    IPC: H04B7/0456 ,  H04B7/08 ,  G06F17/15 ,  H04B7/0413 ,  H04W84/00

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of an autocorrelation calculator. An electronic device including an autocorrelation calculator may be configured to calculate an autocorrelation matrix including an autocorrelation of symbols indicative of a first radio frequency (“RF”) signal and a second RF signal. The electronic device may calculate the autocorrelation matrix based on a stored autocorrelation matrix and the autocorrelation of symbols indicative of the first RF signal and symbols indicative of the second RF signal. The stored autocorrelation matrix may represent another received signal at a different time period than a time period of the first and second RF signals. Examples of the systems and methods may facilitate the processing of data for wireless and may utilize less memory space than a device than a scheme that stores and calculates autocorrelation from a large dataset computed from various time points.

    NEURON CALCULATOR FOR ARTIFICIAL NEURAL NETWORKS
    9.
    发明申请
    NEURON CALCULATOR FOR ARTIFICIAL NEURAL NETWORKS 有权

    公开(公告)号：US20210328631A1

    公开(公告)日：2021-10-21

    申请号：US17362672

    申请日：2021-06-29

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Jaime Cummins ,  Tamara Schmitz ,  Jeremy Chritz

    IPC: H04B7/0413 ,  G06N3/08 ,  G06N3/04

    Abstract: Examples described herein include systems and methods, including wireless devices and systems with neuron calculators that may perform one or more functionalities of a wireless transceiver. The neuron calculator calculates output signals that may be implemented, for example, using accumulation units that sum the multiplicative processing results of ordered sets from ordered neurons with connection weights for each connection between an ordered neuron and outputs of the neuron calculator. The ordered sets may be a combination of some input signals, with the number of signals determined by an order of the neuron. Accordingly, a kth-order neuron may include an ordered set comprising product values of k input signals, where the input signals are selected from a set of k-combinations with repetition. As an example in a wireless transceiver, the neuron calculator may perform channel estimation as a channel estimation processing component of the receiver portion of a wireless transceiver.

    MEMORY DEVICES AND METHODS WHICH MAY FACILITATE TENSOR MEMORY ACCESS
    10.
    发明申请
    MEMORY DEVICES AND METHODS WHICH MAY FACILITATE TENSOR MEMORY ACCESS 有权

    公开(公告)号：US20210165732A1

    公开(公告)日：2021-06-03

    申请号：US17150675

    申请日：2021-01-15

    Applicant: Micron Technology, Inc.

    Inventor： Fa-Long Luo ,  Jaime Cummins ,  Tamara Schmitz ,  Jeremy Chritz

    IPC: G06F12/02 ,  G06F12/0864 ,  G06F12/0893

    Abstract: Methods, apparatuses, and systems for tensor memory access are described. Multiple data located in different physical addresses of memory may be concurrently read or written by, for example, employing various processing patterns of tensor or matrix related computations. A memory controller, which may comprise a data address generator, may be configured to generate a sequence of memory addresses for a memory access operation based on a starting address and a dimension of a tensor or matrix. At least one dimension of a tensor or matrix may correspond to a row, a column, a diagonal, a determinant, or an Nth dimension of the tensor or matrix. The memory controller may also comprise a buffer configured to read and write the data generated from or according to a sequence of memory of addresses.

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