MULTIPLY-ACCUMULATE OPERATION METHOD AND APPARATUS

    公开(公告)号:US20240176590A1

    公开(公告)日:2024-05-30

    申请号:US18522797

    申请日:2023-11-29

    Inventor: Jin-Ho HAN

    CPC classification number: G06F7/5443 G06F5/01 G06F7/483

    Abstract: An embodiment of the present disclosure may provide a multiply-accumulate operation method performed by a multiply-accumulate operation apparatus, the multiply-accumulate operation method including accumulating, by an accumulation register, a value within a preset bit value of a mantissa bitwidth in a result of an addition operation of a shifted first mantissa value and a shifted second mantissa value, determining, by an overflow counter, an overflow count based on an overflow value by which the result of the addition operation of the shifted first mantissa value and the shifted second mantissa value exceeds the preset bit value of the mantissa bitwidth, performing normalization and rounding based on the value accumulated in the accumulation register and the overflow count, and updating, by an exponent updater, the exponent using a normalized and rounded value.

    APPARATUS FOR CORRECTING DYE MIXING RATIO AND METHOD THEREOF

    公开(公告)号:US20240175202A1

    公开(公告)日:2024-05-30

    申请号:US18518745

    申请日:2023-11-24

    Inventor: Hyun Woo OH

    CPC classification number: D06P1/0032 G01J3/463 G01J2003/467

    Abstract: The present invention relates to an apparatus for correcting a dye mixing ratio, the apparatus including a memory, and a processor connected to the memory, wherein, upon receiving a dyeing order including a first computer color matching (CCM) colorimetric value requested by a client, the processor uses at least one of the first CCM colorimetric value, a currently selected dye mixing ratio, a second CCM colorimetric value measured in a dyeing process, fabric characteristic data, and dye characteristic data and corrects the dye mixing ratio so that deviation between the first CCM colorimetric value and the second CCM colorimetric value is minimized.

    APPARATUS FOR RECEIVING DATA FROM MEMORY
    218.
    发明公开

    公开(公告)号:US20240163139A1

    公开(公告)日:2024-05-16

    申请号:US18506544

    申请日:2023-11-10

    CPC classification number: H04L25/03057 G06F13/16 H04L25/0272 G06F2213/16

    Abstract: Disclosed herein is an apparatus for receiving data from memory. The apparatus receives a data signal and a clock signal output from memory and includes a Decision Feedback Equalizer (DFE) including two or more differential signal path units configured to determine and output an output value corresponding to the data signal. Each of the two or more differential signal path units may determine a current output value by reflecting a previous output value fed back from a different one of the two or more differential signal path units in such a way that they operate at different clocks, and may include an offset control unit configured to adjust an offset at an input stage and a feedback control unit configured to change a load of an output stage using the previous output value fed back from the different one of the two or more differential signal path units.

    MULTITASK LEARNING APPARATUS AND METHOD FOR HETEROGENEOUS SPARSE DATASETS

    公开(公告)号:US20240160930A1

    公开(公告)日:2024-05-16

    申请号:US18509790

    申请日:2023-11-15

    Inventor: Jiwon YANG

    CPC classification number: G06N3/08 G06N3/04

    Abstract: Provided are a multitask learning apparatus and method for improving learning performance of heterogeneous small datasets. The multitask learning apparatus includes a first layer configured to generate feature vectors by projecting training data pairs generated from different tasks to one feature space, a second layer configured to extract a common feature from the projected feature vectors, and a third layer configured to draw each individual inference from the extracted common feature. Here, the first layer and the third layer are task-specific layers, and the second layer is a layer shared between tasks. The first layer, the second layer, and the third layer perform forward propagation in one artificial neural network.

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