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公开(公告)号：US10210464B2
公开(公告)日：2019-02-19
申请号：US14856481
申请日：2015-09-16
Applicant: QUALCOMM Incorporated
Inventor： David Jonathan Julian , Anthony Sarah
Abstract: A method of online training of a classifier includes determining a distance from one or more feature vectors of an object to a first predetermined decision boundary established during off-line training for the classifier. The method also includes updating a decision rule as a function of the distance. The method further includes classifying a future example based on the updated decision rule.
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12.发明申请SYSTEM AND METHOD FOR TRANSMTTING AND RECEIVING SIGNAL WITH QUASI-PERIODIC PULSE SEQUENCE 有权用定期脉冲序列传输和接收信号的系统和方法公开(公告)号：US20140219395A1
公开(公告)日：2014-08-07
申请号：US14250259
申请日：2014-04-10
Applicant: Qualcomm Incorporated
Inventor： Petru Cristian Budianu , Jun Shi , David Jonathan Julian
IPC: H04L25/49
CPC classification number: H04L25/49 , H04B1/7174 , H04B1/7183 , H04B2001/6908
Abstract: System and method are disclosed for synchronization of a transmitting device and a receiving device that communicate with each other via pulse modulation. The synchronization technique entails the transmitting device sending one or more quasi-periodic pulse sequences to the receiving device. A quasi-periodic pulse sequence is based on a substantially periodic pulse sequence, and may include some non-periodic pulses or not include some periodic pulses. The transmitting device may transmit frames each including a preamble that comprises one or more quasi-periodic pulse sequences, and a data payload that may comprise data. The receiving device receives the signal, generates samples of the signal, and detects the quasi-periodic pulse sequences in the received signal by analyzing samples based on a sample associated with a pulse and the period associated with the substantially periodic pulse sequence. The receiving device is further able to detect frames based on the detection of the sequence, and extract data therefrom.
Abstract translation: 公开了用于通过脉冲调制相互通信的发送设备和接收设备的同步的系统和方法。 同步技术需要发送设备向接收设备发送一个或多个准周期脉冲序列。 准周期性脉冲序列基于基本上周期性的脉冲序列，并且可以包括一些非周期脉冲或不包括一些周期脉冲。 发送设备可以发送各自包括包括一个或多个准周期性脉冲序列的前同步码的帧和可以包括数据的数据有效载荷。 接收装置接收信号，产生信号样本，并且通过基于与脉冲相关联的样本和与基本周期性脉冲序列相关联的周期来分析样本来检测接收信号中的准周期脉冲序列。 接收装置还能够根据序列的检测来检测帧，并从中提取数据。
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公开(公告)号：US20130252659A1
公开(公告)日：2013-09-26
申请号：US13899019
申请日：2013-05-21
Applicant: QUALCOMM Incorporated
Inventor： Zhanfeng Jia , David Jonathan Julian
IPC: H04W52/04
CPC classification number: H04W52/04 , H04B1/1615 , H04W48/16 , H04W52/0274 , Y02D70/142 , Y02D70/144 , Y02D70/146 , Y02D70/23 , Y02D70/26 , Y02D70/40
Abstract: A duty cycle scheme for wireless communication employs three or more duty cycle levels. In some aspects, a wireless device may continually scan for signals in an active state associated with a first duty cycle, periodically scan for signals during a periodic state associated with a second duty cycle, and periodically scan for signals during a standby state associated with a third duty cycle. Here, the second duty cycle may be lower than the first duty cycle and the third duty cycle may be lower than the second duty cycle. In some aspects the timing of different states may be correlated. In some aspects each wireless in a system may independently control its duty cycle states.
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公开(公告)号：US10373050B2
公开(公告)日：2019-08-06
申请号：US14920099
申请日：2015-10-22
Applicant: QUALCOMM Incorporated
Inventor： Dexu Lin , Venkata Sreekanta Reddy Annapureddy , David Edward Howard , David Jonathan Julian , Somdeb Majumdar , William Richard Bell, II
Abstract: A method of quantizing a floating point machine learning network to obtain a fixed point machine learning network using a quantizer may include selecting at least one moment of an input distribution of the floating point machine learning network. The method may also include determining quantizer parameters for quantizing values of the floating point machine learning network based at least in part on the at least one selected moment of the input distribution of the floating point machine learning network to obtain corresponding values of the fixed point machine learning network.
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公开(公告)号：US10043112B2
公开(公告)日：2018-08-07
申请号：US14528935
申请日：2014-10-30
Applicant: QUALCOMM Incorporated
Inventor： Sachin Subhash Talathi , David Jonathan Julian
Abstract: A method for image processing includes determining features of multiple stored images from a pre-trained deep convolutional network. The method also includes clustering each image of the multiple stored images based on the determined features.
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Patent Agency Ranking
16.发明申请SYSTEM AND METHOD OF ASSOCIATING DEVICES BASED ON ACTUATION OF INPUT DEVICES AND SIGNAL STRENGTH 有权基于输入设备的启动和信号强度的相关设备的系统和方法公开(公告)号：US20150017951A1
公开(公告)日：2015-01-15
申请号：US14504595
申请日：2014-10-02
Applicant: QUALCOMM Incorporated
Inventor： Avneesh Agrawal , Chong Uk Lee , Kamran Moallemi , David Jonathan Julian , Manuel Eduardo Jaime , Robert Keith Douglas , Lu Xiao , Gregory Gordon Rose
CPC classification number: H04W76/14 , A61B5/0015 , A61B5/0404 , G01S13/0209 , G01S13/284 , G01S13/765 , H04B5/0031 , H04L63/0861 , H04L67/24 , H04W4/02 , H04W4/023 , H04W4/027 , H04W4/50 , H04W8/005 , H04W12/06
Abstract: Various operations may be performed based on a distance-related function associated with two or more devices. For example, an association procedure for two or more devices may be based on one or more determined distances. Similarly, presence management may be based on one or more determined distances. A distance-related function may take various form including, for example, a distance between devices, two or more distances between devices, a rate of change in a relative distance between devices, relative acceleration between devices, or some combination of two or more of the these distance-related functions.
Abstract translation: 可以基于与两个或更多个设备相关联的距离相关功能来执行各种操作。 例如，两个或多个设备的关联过程可以基于一个或多个确定的距离。 类似地，存在管理可以基于一个或多个确定的距离。 距离相关功能可以采取各种形式，包括例如设备之间的距离，设备之间的两个或更多个距离，设备之间的相对距离的变化率，设备之间的相对加速度，或两个或更多个 这些距离相关的功能。
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公开(公告)号：US10339447B2
公开(公告)日：2019-07-02
申请号：US14449101
申请日：2014-07-31
Applicant: QUALCOMM Incorporated
Abstract: A method for selecting a reduced number of model neurons in a neural network includes generating a first sparse set of non-zero decoding vectors. Each of the decoding vector is associated with a synapse between a first neuron layer and a second neuron layer. The method further includes implementing the neural network only with selected model neurons in the first neuron layer associated with the non-zero decoding vectors.
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公开(公告)号：US10318848B2
公开(公告)日：2019-06-11
申请号：US15247805
申请日：2016-08-25
Applicant: QUALCOMM Incorporated
Abstract: A method of training for image classification includes labelling a crop from an image including an object of interest. The crop may be labelled with an indication of whether the object of interest is framed, partially framed or not present in the crop. The method may also include assigning a fully framed class to the labelled crop, including the object of interest, if the object of interest is framed. A labelled crop may be assigned a partially framed class if the object of interest is partially framed. A background class may be assigned to a labelled crop if the object of interest is not present in the crop.
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公开(公告)号：US10275719B2
公开(公告)日：2019-04-30
申请号：US14848296
申请日：2015-09-08
Applicant: QUALCOMM Incorporated
Inventor： Sachin Subhash Talathi , David Jonathan Julian
Abstract: Hyper-parameters are selected for training a deep convolutional network by selecting a number of network architectures as part of a database. Each of the network architectures includes one or more local logistic regression layer and is trained to generate a corresponding validation error that is stored in the database. A threshold error for identifying a good set of network architectures and a bad set of network architectures may be estimated based on validation errors in the database. The method also includes choosing a next potential hyper-parameter, corresponding to a next network architecture, based on a metric that is a function of the good set of network architectures. The method further includes selecting a network architecture, from among next network architectures, with a lowest validation error.
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公开(公告)号：US10140573B2
公开(公告)日：2018-11-27
申请号：US14268372
申请日：2014-05-02
Applicant: QUALCOMM Incorporated
Inventor： David Jonathan Julian , Ilwoo Chang
Abstract: Methods and apparatus are provided for processing in an artificial nervous system. According to certain aspects, resolution of one or more functions performed by processing units of a neuron model may be reduced, based at least in part on availability of computational resources or a power target or budget. The reduction in resolution may be compensated for by adjusting one or more network weights.
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