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    METHOD AND SYSTEM FOR GENERATING A DEPTH MAP
    242.
    发明申请
    METHOD AND SYSTEM FOR GENERATING A DEPTH MAP 有权

    公开(公告)号：US20220383530A1

    公开(公告)日：2022-12-01

    申请号：US17772205

    申请日：2020-10-27

    Applicant: RAMOT AT TEL-AVIV UNIVERSITY LTD.

    Inventor： Raja GIRYES ,  Yotam GIL ,  Shay ELMALEM ,  Harel HAIM

    IPC: G06T7/593 ,  G06T7/80

    Abstract: A system for depth estimation, comprises at least a first and a second depth estimation optical systems, each configured for receiving a light beam from a scene and estimating depths within the scene, wherein the first system is a monocular depth estimation optical system; and an image processor, configured for receiving depth information from the first and second systems, and generating a depth map or a three-dimensional image of the scene based on the received depth information.

    Reduction of peak to average power ratio
    246.
    发明授权
    Reduction of peak to average power ratio 有权

    公开(公告)号：US11469935B2

    公开(公告)日：2022-10-11

    申请号：US17194295

    申请日：2021-03-07

    Applicant: RAMOT AT TEL AVIV UNIVERSITY LTD.

    Inventor： Dani Raphaeli ,  Or Levi

    IPC: H04L27/26 ,  H04L5/00

    Abstract: A method for Peak to Average Power Ratio (PAPR) reduction at an input of analog to digital converter (ADC) of the receiver, the method includes mapping, by a mapper, an input symbol to an output symbol that maintains a peak power constraint at the input of the ADC; wherein the mapping is responsive to (a) previously transmitted symbols and (b) a state of the channel following a transmission of the current output symbol; transmitting the output symbol by the transmitter; receiving, by the receiver, a received symbol that represents the output symbol; and de-mapping the received symbol, by a de-mapper of the receiver, to a de-mapped symbol that represents the input symbol.

    DETERMINING TRIANGLES IN GRAPH DATA STRUCTURES USING CROSSPOINT ARRAY
    247.
    发明申请
    DETERMINING TRIANGLES IN GRAPH DATA STRUCTURES USING CROSSPOINT ARRAY 有权

    公开(公告)号：US20220300575A1

    公开(公告)日：2022-09-22

    申请号：US17207912

    申请日：2021-03-22

    Applicant: International Business Machines Corporation ,  Ramot at Tel Aviv University Ltd.

    Inventor： Vasileios Kalantzis ,  Shashanka Ubaru ,  Haim Avron ,  Lior Horesh

    IPC: G06F17/16 ,  G06F16/901 ,  G06F16/22 ,  G06F16/23

    Abstract: Techniques for determining a count of triangles (tr) in a graph data structure using a crosspoint array is described. An adjacency matrix (a) representing the graph is mapped to the crosspoint array by configuring resistance values of crosspoint devices in the array. The count of triangles is initialized to zero (tr=0), and iteratively updated. The updating includes generating a first vector (x1) stochastically to include digital values in a predetermined range, which are converted into the voltage values. A multiplication of the adjacency matrix and the first vector (ax1) is computed using the crosspoint array. A second voltage vector (z1=ax1) is generated that includes voltage values representing the multiplication result. The adjacency matrix and the second voltage vector (z2=az1) are multiplied using the crosspoint array. The computer updates the number of triangles in the graph data structure as tr=tr+Z1T.

    PERMUTATION SELECTION FOR DECODING OF ERROR CORRECTION CODES
    250.
    发明申请
    PERMUTATION SELECTION FOR DECODING OF ERROR CORRECTION CODES 有权

    公开(公告)号：US20220231785A1

    公开(公告)日：2022-07-21

    申请号：US17571659

    申请日：2022-01-10

    Applicant: Ramot at Tel-Aviv University Ltd. ,  Bar-Ilan University

    Inventor： Yair BEERY ,  Nir RAVIV ,  Tomer RAVIV ,  Jacob GOLDBERGER ,  Avi CACIULARU

    IPC: H04L1/00

    Abstract: Disclosed herein is a neural network based pre-decoder comprising a permutation embedding engine, a permutation classifier each comprising one or more trained neural networks and a selection unit. The permutation embedding engine is trained to compute a plurality of permutation embedding vectors each for a respective one of a plurality of permutations of a received codeword encoded using an error correction code and transmitted over a transmission channel subject to interference. The permutation classifier is trained to compute a decode score for each of the plurality of permutations expressing its probability to be successfully decoded based on classification of the plurality of permutation embedding vectors coupled with the plurality of permutations. The selection unit is configured to output one or more selected permutations having a highest decode score. One or more decoders may be then applied to recover the encoded codeword by decoding the one or more selected permutations.

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