公开(公告)号：US10552734B2

公开(公告)日：2020-02-04

申请号：US14325169

申请日：2014-07-07

Applicant: QUALCOMM Incorporated

Inventor： Naveen Gandham Rao ,  Michael Campos ,  Yinyin Liu

IPC: G06N3/08

Abstract: A method of dynamically modifying target selection with a neural network includes dynamically modifying a selection function by controlling an amount of imbalance of connections in the neural network. A selected neuron represents one of multiple candidate targets.

公开(公告)号：US09460384B2

公开(公告)日：2016-10-04

申请号：US14260140

申请日：2014-04-23

Applicant: QUALCOMM Incorporated

Inventor： Jeffrey Alexander Levin ,  Yinyin Liu ,  Sarah Paige Gibson ,  Michael Campos ,  Vikram Gupta ,  Victor Hokkiu Chan ,  Edward Hanyu Liao ,  Erik Christopher Malone

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/049

Abstract: Methods and apparatus are provided for effecting modulation using global scalar values in a spiking neural network. One example method for operating an artificial nervous system generally includes determining one or more updated values for artificial neuromodulators to be used by a plurality of entities in a neuron model and providing the updated values to the plurality of entities.

Abstract translation: 提供了方法和装置，用于在加标神经网络中使用全局标量值进行调制。 用于操作人造神经系统的一个示例性方法通常包括确定将由神经元模型中的多个实体使用的人造神经调节器的一个或多个更新值，并向多个实体提供更新的值。

公开(公告)号：US09147157B2

公开(公告)日：2015-09-29

申请号：US13669521

申请日：2012-11-06

Applicant: QUALCOMM Incorporated

Inventor： Michael Campos

IPC: G06F15/18 ,  G06N3/04

CPC classification number: G06N3/049

Abstract: Certain aspects of the present disclosure provide methods and apparatus for identifying spectral peaks in a neuronal spiking representation of a signal, such as an auditory signal. One example method generally includes receiving a signal; filtering the signal into a plurality of channels using a plurality of filters having different frequency passbands; sending the filtered signal in each of the channels to a first type of spiking neuron model; sending the filtered signal in each of the channels to a second type of spiking neuron model; and identifying one or more spectral peaks in the signal based on a first output of the first type of spiking neuron model and a second output of the second type of spiking neuron model for each of the channels.

Abstract translation: 本公开的某些方面提供用于识别诸如听觉信号的信号的神经元尖峰表示中的光谱峰的方法和装置。 一个示例性方法通常包括接收信号; 使用具有不同频率通带的多个滤波器将信号滤波成多个信道; 将每个信道中的滤波信号发送到第一类型的加标神经元模型; 将每个信道中的滤波信号发送到第二类型的加标神经元模型; 以及基于第一类型的加标神经元模型的第一输出和用于每个通道的第二类型加标神经元模型的第二输出来识别信号中的一个或多个频谱峰。

公开(公告)号：US09721204B2

公开(公告)日：2017-08-01

申请号：US14065388

申请日：2013-10-28

Applicant: QUALCOMM Incorporated

Inventor： Michael Campos ,  Casimir Matthew Wierzynski ,  Bardia Fallah Behabadi

IPC: G06F15/00 ,  G06F17/00 ,  G06N3/10 ,  G06N3/08 ,  G06N3/04 ,  G08B17/00

CPC classification number: G06N3/082 ,  G06N3/04 ,  G06N3/049 ,  G06N3/10 ,  G06N3/105 ,  G08B17/005

Abstract: An artificial neural network may be configured to test the impact of certain input parameters. To improve testing efficiency and to avoid test runs that may not alter system performance, the effect of input parameters on neurons or groups of neurons may be determined to classify the neurons into groups based on the impact of certain parameters on those groups. Groups may be ordered serially and/or in parallel based on the interconnected nature of the groups and whether the output of neurons in one group may affect the operation of another. Parameters not affecting group performance may be pruned as inputs to that particular group prior to running system tests, thereby conserving processing resources during testing.

公开(公告)号：US20140129497A1

公开(公告)日：2014-05-08

申请号：US13669534

申请日：2012-11-06

Applicant: QUALCOMM INCORPORATED

Inventor： Michael Campos

IPC: G06N3/08

CPC classification number: G06N3/049

Abstract: Certain aspects of the present disclosure provide methods and apparatus for performing onset detection in a neuronal spiking representation of a signal, such as an auditory signal. One example method generally includes receiving a signal; filtering the signal into a plurality of channels using a plurality of filters having different frequency passbands; sending the filtered signal in each of the channels to a first type of spiking neuron model; sending the filtered signal in each of the channels to a second type of spiking neuron model; and detecting one or more onsets of the signal based on a first output of the first type of spiking neuron model and a second output of the second type of spiking neuron model for each of the channels.

Abstract translation: 本公开的某些方面提供了用于在诸如听觉信号的信号的神经元尖峰表示中执行开始检测的方法和装置。 一个示例性方法通常包括接收信号; 使用具有不同频率通带的多个滤波器将信号滤波成多个信道; 将每个信道中的滤波信号发送到第一类型的加标神经元模型; 将每个信道中的滤波信号发送到第二类型的加标神经元模型; 以及基于所述第一类型的加标神经元模型的第一输出和所述每个信道的所述第二类型的刺激神经元模型的第二输出来检测所述信号的一个或多个开始。

公开(公告)号：US09269045B2

公开(公告)日：2016-02-23

申请号：US14286556

申请日：2014-05-23

Applicant: QUALCOMM Incorporated

Inventor： Lakshmi Krishnan ,  Michael Campos

IPC: G10L15/00 ,  G10L21/00 ,  G10L25/90 ,  G10L19/00 ,  G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06N3/049 ,  G10L21/0272 ,  G10L25/30 ,  G10L25/78

Abstract: A method of audio source segregation includes selecting an audio attribute of an audio signal. The method also includes representing a portion of the audio attribute that is dominated by a single source as a source spiking event. In addition, the method includes representing a remaining portion of the audio signal as an audio signal spiking event. The method further includes determining whether the remaining portion coincides with the single source based on coincidence of the source spiking event and audio signal spiking event.

Abstract translation: 音频源隔离的方法包括选择音频信号的音频属性。 该方法还包括将由单个源主导的音频属性的一部分表示为源尖峰事件。 此外，该方法包括将音频信号的剩余部分表示为音频信号尖峰事件。 该方法还包括基于源尖峰事件和音频信号尖峰事件的一致性确定剩余部分是否与单个源重合。

公开(公告)号：US20140129495A1

公开(公告)日：2014-05-08

申请号：US13669516

申请日：2012-11-06

Applicant: QUALCOMM INCORPORATED

Inventor： Michael Campos

IPC: G06N3/08

CPC classification number: G06N3/049

Abstract: Certain aspects of the present disclosure provide methods and apparatus for transducing a signal into a neuronal spiking representation using at least two distinct populations of spiking neuron models. One example method generally includes receiving a signal; filtering the signal into a plurality of channels using a plurality of filters having different frequency passbands; sending the filtered signal in each of the channels to a first type of spiking neuron model; and sending the filtered signal in each of the channels to a second type of spiking neuron model, wherein the second type differs from the first type of spiking neuron model in at least one parameter.

Abstract translation: 本公开的某些方面提供了使用至少两个不同种群的加标神经元模型将信号转换成神经元尖峰表示的方法和装置。 一个示例性方法通常包括接收信号; 使用具有不同频率通带的多个滤波器将信号滤波成多个信道; 将每个信道中的滤波信号发送到第一类型的加标神经元模型; 并将每个信道中的滤波信号发送到第二类型的加标神经元模型，其中第二类型与至少一个参数中的第一类型的加标神经元模型不同。