公开(公告)号：US20140334726A1

公开(公告)日：2014-11-13

申请号：US13888802

申请日：2013-05-07

Applicant: Qualcomm Technologies, Inc.

Inventor： Christophe Bernard ,  Sarah Lannes

IPC: G06T5/00

CPC classification number: G06T5/002 ,  G06T7/0002 ,  G06T2207/10024 ,  G06T2207/20016 ,  G06T2207/20021 ,  G06T2207/20064 ,  G06T2207/20182 ,  G06T2207/30168

Abstract: A method for determining noise levels in a subband of an image. The method comprises receiving the subband of the image, defining block regions in at least two space domains of the subband, for each defined block region, identifying first wavelet coefficients associated with coordinate values in the at least two space domains in the defined block region, computing a correlation matrix between identified wavelet coefficients to determine the correlation between first wavelet coefficients according to the at least one color domain, computing second wavelet coefficients, the computation of second wavelet coefficients being based on the correlation matrix and the first wavelet coefficients, computing at least one noise level, the noise level computation being based on at least one second wavelet coefficient and providing the at least one noise level.

Abstract translation: 一种用于确定图像的子带中的噪声水平的方法。 该方法包括接收图像的子带，为每个定义的块区域定义子带的至少两个空间域中的块区域，识别与所定义的块区域中的至少两个空间域中的坐标值相关联的第一小波系数， 计算确定的小波系数之间的相关矩阵，以确定根据至少一个色域的第一小波系数之间的相关性，计算第二小波系数，基于相关矩阵的第二小波系数的计算和第一小波系数， 至少一个噪声电平，所述噪声电平计算基于至少一个第二小波系数并提供所述至少一个噪声电平。

公开(公告)号：US20140143531A1

公开(公告)日：2014-05-22

申请号：US13680399

申请日：2012-11-19

Applicant: QUALCOMM TECHNOLOGIES, INC. ,  ARTERIS SAS

Inventor： Jean-Jacques Lecler

IPC: G06F9/445

CPC classification number: G06F9/445 ,  G06F9/3875 ,  G06F17/505 ,  G06F2217/84

Abstract: The optimal configuration of a number of optional pipeline stages within the data paths of systems-on-chip is determined by application of a solver. The solver includes variables such as: the placement of modules physically within the floorplan of the chip; the signal propagation time; the logic gate switching time; the arrival time, after a clock edge, of a signal at each module port; the arrival time at each pipeline stage; and the Boolean value of the state of activation of each optional pipeline stage. The optimal configuration ensures that a timing constraint is met, if possible, with the lowest possible cost of pipeline stages.

Abstract translation: 通过应用求解器确定片上系统的数据路径内的多个可选流水线级的最佳配置。 求解器包括以下变量：将模块物理放置在芯片的平面图中; 信号传播时间; 逻辑门切换时间; 每个模块端口的信号到达时间，时钟沿之后; 每个流水线阶段的到达时间; 以及每个可选流水线阶段的激活状态的布尔值。 最佳配置确保了在可能的情况下满足流水线阶段可能的最低成本的时序约束。

公开(公告)号：US12231302B2

公开(公告)日：2025-02-18

申请号：US18452492

申请日：2023-08-18

Applicant: QUALCOMM Technologies, Inc.

Inventor： Vijaya Datta Mayyuri ,  An Chen

IPC: H04L41/16 ,  G06F18/214 ,  H04W8/18 ,  H04W8/20 ,  H04W8/24

Abstract: A method for managing model updates by a first zone server, associated with a first zone model of a plurality of zone models, includes receiving a global model from a global server associated with the global model. The method also includes transmitting the global model to user equipment (UEs) in a first group of UEs associated with the first zone model. The method further includes receiving, from one or more UEs in the first group, model updates associated with the global model based on transmitting the global model. The method further includes transmitting, to the global server, an average of the model updates received from the one or more UEs. The method also includes updating the global model to generate the first zone model based on the model updates. The method further includes transmitting the first zone model to one or more UEs in the first group.

公开(公告)号：US12211276B2

公开(公告)日：2025-01-28

申请号：US17526969

申请日：2021-11-15

Applicant: QUALCOMM Technologies, Inc.

Inventor： Christen Maximilian Filtenborg ,  Deepak Kumar Gupta

IPC: G06V20/40 ,  G06F40/30 ,  G06N3/04 ,  G06V10/44 ,  G06V10/94

Abstract: A computer-implemented method for tracking with visual object constraints includes receiving a lingual constraint and a video. A word embedding is generated based on the lingual constraint. A set of features is extracted for one or more frames of the video. The word embedding is cross-correlated to the set of features for the one or more frames of the video. A prediction indicating whether the lingual constraint is in the one or more frames of the video is generated based on the cross-correlation.

公开(公告)号：US12056615B2

公开(公告)日：2024-08-06

申请号：US17030361

申请日：2020-09-23

Applicant: QUALCOMM Technologies, Inc.

Inventor： Berkay Kicanaoglu ,  Taco Sebastiaan Cohen ,  Pim De Haan

IPC: G06N3/082 ,  G06N3/045 ,  G06T3/10

CPC classification number: G06N3/082 ,  G06N3/045 ,  G06T3/10

Abstract: A method for generating a convolutional neural network to operate on a spherical manifold, generates locally-defined gauges at multiple positions on the spherical manifold. A convolution is defined at each of the positions on the spherical manifold with respect to an arbitrarily selected locally-defined gauge. The results of the convolution that is defined at each position based on gauge equivariance is translated to obtain a manifold convolution.

公开(公告)号：US20240176994A1

公开(公告)日：2024-05-30

申请号：US18551844

申请日：2021-07-26

Applicant: QUALCOMM TECHNOLOGIES, INC.

Inventor： Phillip LIPPE ,  Taco Sebastiaan COHEN ,  Efstratios GAVVES

IPC: G06N3/0464 ,  G06N3/09

CPC classification number: G06N3/0464 ,  G06N3/09

Abstract: A method for generating a causal graph includes receiving a data set including observation data and intervention data corresponding to multiple variables. A probability distribution is determined for each variable based on the observation data. A likelihood of including each edge in the graph is computed based on the probability distribution and the intervention data. Each edge is a causal connection between variables of the multiple variables. The graph is generated based on the likelihood of including each edge. The graph may be updated by iteratively repeating the determination of the probability distribution and the computing of the likelihood of including each edge.

公开(公告)号：US11917493B2

公开(公告)日：2024-02-27

申请号：US17837944

申请日：2022-06-10

Applicant: Qualcomm Technologies Inc.

Inventor： Felix Markhovsky ,  Truman Prevatt ,  Russ Markhovsky ,  David Goodwin Shaw ,  Tyler Matthew Smith

IPC: H04W4/029 ,  H04W64/00 ,  H04B17/336 ,  H04W24/10 ,  H04L43/0864 ,  G01S5/06 ,  H04B17/27 ,  G01S5/10 ,  G01S5/00 ,  G01S5/02 ,  H04W4/02

CPC classification number: H04W4/029 ,  G01S5/00 ,  G01S5/0273 ,  G01S5/06 ,  G01S5/10 ,  H04B17/27 ,  H04B17/336 ,  H04L43/0864 ,  H04W4/025 ,  H04W24/10 ,  H04W64/00

Abstract: UE location determined by collecting and preprocessing signal data at a detector and sending extracted data to a remote locate server. The detector buffers samples from signals provided by receive channels, detects known reference signals from receive channels based on reference signal parameters, isolates symbols carrying the reference signal from frames, extracts data from symbols, and sends extracted data to locate server. The locate server receives the extracted data, estimates locate observables based on the extracted data and calculates the UE location based on the estimated locate observables, the reference signal parameters and the extracted data. The detector and/or the server may also generate correlation coefficients between reference signals carrying spectrum received from a serving cell and utilize the correlation coefficients to cancel a serving cell signal in symbols that include known in advance reference signals from the serving cell and one or more neighboring cells of the wireless system.

公开(公告)号：US20230422624A1

公开(公告)日：2023-12-28

申请号：US18247869

申请日：2021-12-03

Applicant: QUALCOMM Technologies, Inc.

Inventor： Robert John LITTRELL ,  Craig CORE

IPC: H10N30/853 ,  H04R17/02 ,  H10N30/05 ,  H10N30/074 ,  H10N30/30

CPC classification number: H10N30/853 ,  H04R17/02 ,  H10N30/306 ,  H10N30/074 ,  H10N30/05

Abstract: A low noise piezoelectric sensor, such as a piezoelectric acoustic transducer, includes a first conductive layer, a second conductive layer, and a piezoelectric layer between the first conductive layer and the second conductive layer. The piezoelectric layer comprises aluminum scandium nitride (AlScN) having a scandium content of greater than 15%, in which the scandium content and an aluminum content comprises 100% of the aluminum scandium nitride. In this way, the piezoelectric layer (or the sensor including the piezoelectric layer) achieves a dissipation factor of less than about 0.1%.

公开(公告)号：US11835639B2

公开(公告)日：2023-12-05

申请号：US15595702

申请日：2017-05-15

Applicant: QUALCOMM TECHNOLOGIES, INC.

Inventor： Felix Markhovsky ,  Truman Prevatt ,  Russ Markhovsky

IPC: G01S5/02 ,  H04W4/02 ,  H04W56/00 ,  G01S1/04 ,  G01S1/20 ,  G01S3/74 ,  G01S13/74

CPC classification number: G01S5/0218 ,  G01S1/0423 ,  G01S1/20 ,  G01S3/74 ,  G01S5/021 ,  G01S5/0205 ,  G01S5/0215 ,  G01S5/0226 ,  G01S5/0257 ,  G01S13/74 ,  H04W4/023 ,  H04W56/001 ,  G01S5/0252

Abstract: Systems and methods for determining a location of one or more user equipment (UE) in a wireless system can comprise receiving reference signals via a location management unit having two or more co-located channels, wherein the two or more co-located channels are tightly synchronized with each other and utilizing the received reference signals to calculate a location of at least one UE among the one or more UE. Embodiments include multichannel synchronization with a standard deviation of less than or equal 10 ns. Embodiments can include two LMUs, with each LMU having internal synchronization, or one LMU with tightly synchronized signals.

公开(公告)号：US20230385651A1

公开(公告)日：2023-11-30

申请号：US18102601

申请日：2023-01-27

Applicant: QUALCOMM Technologies, Inc.

Inventor： Vijaya Datta MAYYURI ,  An CHEN

IPC: G06N3/098 ,  G06N3/0464

CPC classification number: G06N3/098 ,  G06N3/0464

Abstract: A processor-implemented method includes receiving, by a user equipment (UE), a zone determination function based on registering for a federated learning process for training a first federated learning model. The method also includes determining, by the UE, a zone membership in accordance with UE parameters and the zone determination function. The method further includes selecting the first federated learning model, by the UE, based on the zone membership. The method includes training the first federated learning model by the UE.