公开(公告)号：US20150278685A1

公开(公告)日：2015-10-01

申请号：US14486642

申请日：2014-09-15

Applicant: QUALCOMM Incorporated

Inventor： Thomas Jiaqian ZHENG ,  Jeffrey Clinton SHAW ,  Harinath GARUDADRI

IPC: G06N3/08

CPC classification number: G06N3/049 ,  G06N3/0472

Abstract: A method of using spiking neural network delays to represent sequences includes assigning one or more symbol neurons to each symbol in a dictionary. The method also includes assigning a synapse from each symbol neuron in a group to a particular ngram neuron. A set of synapses associated with the group of symbol neurons comprises a bundle of synapses. In addition, the method includes assigning a delay to each synapse in the bundle. The method further includes representing a symbol sequence based on sequential spiking of symbol neurons and ngram neuron spikes in response to detecting inter event intervals.

Abstract translation: 使用尖峰神经网络延迟来表示序列的方法包括将一个或多个符号神经元分配给字典中的每个符号。 该方法还包括从组中的每个符号神经元向特定的ngram神经元分配突触。 与该组符号神经元相关联的一组突触包括一组突触。 此外，该方法包括为束中的每个突触分配延迟。 该方法还包括响应于检测到事件间隔而基于符号神经元和ngram神经元峰值的顺序尖峰来表示符号序列。

公开(公告)号：US20210169426A1

公开(公告)日：2021-06-10

申请号：US17182096

申请日：2021-02-22

Applicant: QUALCOMM Incorporated

Inventor： Harinath GARUDADRI ,  Pawan Kumar BAHETI

IPC: A61B5/00 ,  G01R13/02 ,  A61B5/1455 ,  G06K9/00 ,  H03M7/30

Abstract: Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.

公开(公告)号：US20190125271A1

公开(公告)日：2019-05-02

申请号：US16227955

申请日：2018-12-20

Applicant: QUALCOMM Incorporated

Inventor： Harinath GARUDADRI ,  Pawan Kumar BAHETI

IPC: A61B5/00 ,  H03M7/30 ,  G06K9/00 ,  A61B5/1455 ,  G01R13/02

Abstract: Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.