Capacitor-less low dropout regulator using dual feedback loop structure

    公开(公告)号:US12007801B2

    公开(公告)日:2024-06-11

    申请号:US17885848

    申请日:2022-08-11

    CPC classification number: G05F1/575 G05F1/565

    Abstract: A capacitor-less low dropout regulator includes: a capacitor-less dual feedback loop unit including a plurality of feedback resistors, an error amplifier, and a transconductance cell to form a main loop passing through the error amplifier and a sub-loop passing through the gm cell without passing through the error amplifier; a dynamic compensation unit connected to a first main pole located at an output of the error amplifier and a second main pole located at an output of the gm cell to provide dynamic frequency compensation using a Miller effect to the first main pole and the second main pole according to a load current of the capacitor-less dual feedback loop unit; and a load current measurement unit configured to measure a load current of a third main pole formed at a load of the dual feedback loop unit to provide the load current to the dynamic compensation unit.

    PROGRAM ANALYSIS DEVICE AND METHOD
    66.
    发明公开

    公开(公告)号:US20240184685A1

    公开(公告)日:2024-06-06

    申请号:US18278503

    申请日:2022-02-25

    CPC classification number: G06F11/3608

    Abstract: The present invention relates to a program analysis device and method, wherein the program analysis device may comprise: a selection unit for selecting one of top-down processing or bottom-up processing for at least one analysis equation among a plurality of analysis equations; a first learning unit which, when the selection unit selects the top-down processing, performs top-down processing for the at least one analysis equation on the basis of a first learning algorithm in response to the selection, and thereby acquires at least one first learned analysis equation; and a second learning unit which, when the selection unit selects the bottom-up processing, performs bottom-up processing for the at least one analysis equation on the basis of a second learning algorithm in response to the selection, and thereby acquires at least one second learned analysis equation.

    LOW-LIGHT IMAGE IMPROVEMENT APPARATUS AND METHOD

    公开(公告)号:US20240161243A1

    公开(公告)日:2024-05-16

    申请号:US18221989

    申请日:2023-07-14

    Abstract: Disclosed are a low-light image improvement apparatus and method. The low-light image improvement apparatus includes: an image component decomposition network module that analyzes a light image, a low-light image, and a mid-light image to decompose reflectance and illumination, respectively, wherein the mid-light image is generated using the light image and the low-light image; and a component improvement network module configured to include a mid-teacher network model that extracts a first feature map with improved reflectance and illumination of the mid-light image using the reflectance and illumination of the light image and a student network module that distills the extracted first feature map and then extracts a second feature map for the reflectance and illumination of the low-light image based on the distilled first feature map and acquires an image with improved light by reflecting a structural component of a multi-band near-infrared image in the second feature map.

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