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    SYSTEM AND METHODS FOR LOW COMPLEXITY LIST DECODING OF TURBO CODES AND CONVOLUTIONAL CODES
    44.
    发明申请
    SYSTEM AND METHODS FOR LOW COMPLEXITY LIST DECODING OF TURBO CODES AND CONVOLUTIONAL CODES 审中-公开

    公开(公告)号：US20190173498A1

    公开(公告)日：2019-06-06

    申请号：US16272722

    申请日：2019-02-11

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Mostafa EL-KHAMY ,  Jinhong WU ,  Jungwon LEE ,  Inyup KANG

    IPC: H03M13/39 ,  G06F11/10

    Abstract: Method for decoding signal includes receiving signal, where signal includes at least one symbol; decoding signal in stages, where each at least one symbol of signal is decoded into at least one bit per stage, wherein Log-Likelihood Ratio (LLR) for each at least one bit at each stage is determined, and identified in vector LAPP; performing Cyclic Redundancy Check (CRC) on LAPP, and stopping if LAPP passes CRC; otherwise, determining magnitudes of LLRs in LAPP; identifying K LLRs in LAPP with smallest magnitudes and indexing K LLRs as r={r(1), r(2), . . . , r(K)}; setting Lmax to maximum magnitude of LLRs in LAPP or maximum possible LLR quantization value; setting v=1; generating {tilde over (L)}A(r(k))=LA(r(k))−Lmaxvksign[LAPP(r(k))], for k=1, 2, . . . , K; decoding with {tilde over (L)}A to identify {tilde over (L)}APP, wherein {tilde over (L)}APP is LLR vector; and performing CRC on {tilde over (L)}APP, and stopping if {tilde over (L)}APP passes CRC or v=2K-1; otherwise, incrementing v and returning to generating {tilde over (L)}A(r(k)).

    SYSTEM AND METHOD FOR A UNIFIED ARCHITECTURE MULTI-TASK DEEP LEARNING MACHINE FOR OBJECT RECOGNITION
    47.
    发明申请
    SYSTEM AND METHOD FOR A UNIFIED ARCHITECTURE MULTI-TASK DEEP LEARNING MACHINE FOR OBJECT RECOGNITION 审中-公开

    公开(公告)号：US20170344808A1

    公开(公告)日：2017-11-30

    申请号：US15224487

    申请日：2016-07-29

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Mostafa EL-KHAMY ,  Arvind YEDLA ,  Marcel NASSAR ,  Jungwon LEE

    IPC: G06K9/00

    CPC classification number: G06K9/00268 ,  G06K9/00228 ,  G06T7/70 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30201

    Abstract: A system to recognize objects in an image includes an object detection network outputs a first hierarchical-calculated feature for a detected object. A face alignment regression network determines a regression loss for alignment parameters based on the first hierarchical-calculated feature. A detection box regression network determines a regression loss for detected boxes based on the first hierarchical-calculated feature. The object detection network further includes a weighted loss generator to generate a weighted loss for the first hierarchical-calculated feature, the regression loss for the alignment parameters and the regression loss of the detected boxes. A backpropagator backpropagates the generated weighted loss. A grouping network forms, based on the first hierarchical-calculated feature, the regression loss for the alignment parameters and the bounding box regression loss, at least one of a box grouping, an alignment parameter grouping, and a non-maximum suppression of the alignment parameters and the detected boxes.

    METHOD AND SYSTEM FOR CONTIGUOUS HARQ MEMORY MANAGEMENT WITH MEMORY SPLITTING
    48.
    发明申请
    METHOD AND SYSTEM FOR CONTIGUOUS HARQ MEMORY MANAGEMENT WITH MEMORY SPLITTING 审中-公开
    用于具有存储器分割的连续HARQ存储器管理的方法和系统

    公开(公告)号：US20160241362A1

    公开(公告)日：2016-08-18

    申请号：US14847320

    申请日：2015-09-08

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Mostafa EL-KHAMY ,  Arvind YEDLA ,  SangHyuck HA ,  Hyunsang CHO ,  lnyup KANG

    IPC: H04L1/18 ,  H04L5/00

    CPC classification number: H04L1/1835 ,  H04L1/1822 ,  H04L5/001 ,  H04L5/0055

    Abstract: Apparatuses (including user equipment (UE) and modem chips for UEs), systems, and methods for UE downlink Hybrid Automatic Repeat reQuest (HARQ) buffer memory management are described. In one method, the entire UE DL HARQ buffer memory space is pre-partitioned according to the number and capacities of the UE's active carrier components. In another method, the UE DL HARQ buffer is split between on-chip and off-chip memory so that each partition and sub-partition is allocated between the on-chip and off-chip memories in accordance with an optimum ratio.

    Abstract translation: 描述了用于UE下行链路混合自动重传请求（HARQ）缓冲存储器管理的装置（包括用于UE的用户设备（UE）和调制解调器芯片），系统和方法。 在一种方法中，根据UE的活动载波分量的数量和容量对整个UE DL HARQ缓冲存储器空间进行预分区。 在另一种方法中，UE DL HARQ缓冲器在片上和片外存储器之间被分割，使得每个分区和子分区根据最佳比例被分配在片上和片外存储器之间。

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