中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

195 records (took 0.033 seconds)

    SYSTEMS FOR ERROR REDUCTION OF ENCODED DATA USING NEURAL NETWORKS
    1.
    发明申请
    SYSTEMS FOR ERROR REDUCTION OF ENCODED DATA USING NEURAL NETWORKS 有权

    公开(公告)号：US20250167811A1

    公开(公告)日：2025-05-22

    申请号：US19028790

    申请日：2025-01-17

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Jaime Cummins

    IPC: H03M13/37 ,  G06F7/544 ,  G06N3/08

    Abstract: Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

    Wireless devices and systems including examples of configuration during an active time period
    2.
    发明授权
    Wireless devices and systems including examples of configuration during an active time period 有权

    公开(公告)号：US12143266B2

    公开(公告)日：2024-11-12

    申请号：US17321283

    申请日：2021-05-14

    Applicant: MICRON TECHNOLOGY, INC.

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

    IPC: H04L41/0813 ,  H04L41/0806 ,  H04L41/0823 ,  H04L41/0859 ,  H04L67/12 ,  H04W76/28

    Abstract: Examples described herein include methods, devices, and systems which may implement different processing stages for wireless communication in processing units. Such data processing may include a source data processing stage, a baseband processing stage, a digital front-end processing stage, and a radio frequency (RF) processing stage. Data may be received from a sensor of device and then processed in the stages to generate output data for transmission. Processing the data in the various stages may occur during an active time period of a discontinuous operating mode. During the active time period, a reconfigurable hardware platform may allocate all or a portion of the processing units to implement the processing stages. Examples of systems and methods described herein may facilitate the processing of data for 5G (e.g., New Radio (NR)) wireless communications in a power-efficient and time-efficient manner.

    SYSTEMS FOR ERROR REDUCTION OF ENCODED DATA USING NEURAL NETWORKS
    5.
    发明公开
    SYSTEMS FOR ERROR REDUCTION OF ENCODED DATA USING NEURAL NETWORKS 审中-公开

    公开(公告)号：US20230163788A1

    公开(公告)日：2023-05-25

    申请号：US18158332

    申请日：2023-01-23

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo ,  Jaime Cummins

    IPC: H03M13/37 ,  G06F7/544

    CPC classification number: H03M13/37 ,  G06F7/5443 ,  G06N3/08

    Abstract: Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

    MIXING COEFFICIENT DATA FOR PROCESSING MODE SELECTION
    6.
    发明申请
    MIXING COEFFICIENT DATA FOR PROCESSING MODE SELECTION 有权

    公开(公告)号：US20230113600A1

    公开(公告)日：2023-04-13

    申请号：US18053310

    申请日：2022-11-07

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo

    IPC: H04B1/401 ,  H04L25/02 ,  H04W72/044 ,  H04L1/00 ,  H04B1/44 ,  G06N3/08 ,  H04B7/08 ,  G06N3/044

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data delayed versions of at least a portion of the respective processing results with coefficient data specific to a processing mode selection. For example, a computing system with processing units may mix the input data delayed versions of respective outputs of various layers of multiplication/accumulation processing units (MAC units) for a transmission in a radio frequency (RF) wireless domain with the coefficient data to generate output data that is representative of the transmission being processed according to a wireless processing mode selection. In another example, such mixing input data with delayed versions of processing results may be to receive and process noisy wireless input data. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

    Self interference noise cancellation to support multiple frequency bands
    8.
    发明授权
    Self interference noise cancellation to support multiple frequency bands 有权

    公开(公告)号：US11552658B2

    公开(公告)日：2023-01-10

    申请号：US16113995

    申请日：2018-08-27

    Applicant: MICRON TECHNOLOGY, INC.

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

    IPC: 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.

    Wireless devices and systems including examples of compensating I/Q imbalance with neural networks or recurrent neural networks
    9.
    发明授权
    Wireless devices and systems including examples of compensating I/Q imbalance with neural networks or recurrent neural networks 有权

    公开(公告)号：US11496341B2

    公开(公告)日：2022-11-08

    申请号：US16992486

    申请日：2020-08-13

    Applicant: MICRON TECHNOLOGY, INC.

    Inventor： Fa-Long Luo

    IPC: H04L25/03 ,  G06N3/04 ,  H04L25/02 ,  G06N3/08

    Abstract: Examples described herein include methods, devices, and systems which may compensate input data for I/Q imbalance or noise related thereto to generate compensated input data. In doing such the above compensation, during an uplink transmission time interval (TTI), a switch path is activated to provide converted input data to a receiver stage including a recurrent neural network (RNN). The RNN may calculate an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate filter coefficient data associated with the I/Q imbalance. The feedback signal is provided, after processing through the receiver, to the RNN. During an uplink TTI, the converted input data may also be transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path may be deactivated and the receiver stage may receive an additional RF wireless transmission to be processed in the receiver stage.

    Methods and apparatus for performing video processing matrix operations within a memory array
    10.
    发明授权
    Methods and apparatus for performing video processing matrix operations within a memory array 有权

    公开(公告)号：US11449577B2

    公开(公告)日：2022-09-20

    申请号：US16689981

    申请日：2019-11-20

    Applicant: Micron Technology, Inc.

    Inventor： Fa-Long Luo

    IPC: G06F17/16 ,  G06F17/14 ,  G11C11/4094 ,  G06F12/02 ,  G06F1/03

    Abstract: Methods and apparatus for performing video processing matrix operations within a memory fabric. Various embodiments of the present disclosure are directed to converting a memory array into a matrix fabric for discrete cosine transform (DCT) matrix transformations and performing DCT matrix operations therein. Exemplary embodiments described herein perform DCT matrix-matrix multiplication operations within a memory device that includes a matrix fabric and matrix multiplication unit (MMU). In one embodiment, matrix-matrix multiplication operations are obtained using separate matrix-vector products. In one exemplary embodiment, the matrix fabric uses a “crossbar” construction of resistive elements. Each resistive element stores a level of impedance that represents the corresponding matrix coefficient value. The crossbar connectivity can be driven with an electrical signal representing the input vector as an analog voltage. The resulting signals can be converted from analog voltages to a digital values by an MMU to yield a vector-matrix product. In some cases, the MMU may additionally perform various other logical operations within the digital domain.

Patent Agency Ranking