公开(公告)号：US20150066826A1

公开(公告)日：2015-03-05

申请号：US14281118

申请日：2014-05-19

Applicant: QUALCOMM INCORPORATED

Inventor： Michael-David Nakayoshi CANOY ,  William Richard BELL, II ,  Ramakrishna KINTADA ,  Venkat RANGAN

IPC: G06N3/06 ,  G06N3/08

CPC classification number: G06N3/10 ,  G06F11/302 ,  G06F11/3636 ,  G06N3/049 ,  G06N3/08

Abstract: Methods and apparatus are provided for using a breakpoint determination unit to examine an artificial nervous system. One example method generally includes operating at least a portion of the artificial nervous system; using the breakpoint determination unit to detect that a condition exists based at least in part on monitoring one or more components in the artificial nervous system; and at least one of suspending, examining, modifying, or flagging the operation of the at least the portion of the artificial nervous system, based at least in part on the detection.

Abstract translation: 提供了使用断点确定单元来检查人造神经系统的方法和装置。 一个示例性方法通常包括操作人造神经系统的至少一部分; 使用所述断点确定单元至少部分地基于监视所述人造神经系统中的一个或多个组件来检测状况存在; 以及至少部分地基于所述检测来暂停，检查，修改或标记所述至少所述人造神经系统的所述部分的操作中的至少一个。

公开(公告)号：US20160328646A1

公开(公告)日：2016-11-10

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

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06K9/4628 ,  G06N3/04 ,  G06N3/06 ,  G06N3/10

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.

Abstract translation: 使用量化器来量化浮点计算机学习网络以获得定点机器学习网络的方法可以包括选择浮点计算机学习网络的输入分布的至少一个时刻。 该方法还可以包括：至少部分地基于浮点机器学习网络的输入分布的至少一个选定时刻来确定用于量化浮点计算机学习网络的值的量化器参数，以获得固定点计算机的相应值 学习网络

公开(公告)号：US20150278683A1

公开(公告)日：2015-10-01

申请号：US14228078

申请日：2014-03-27

Applicant: QUALCOMM Incorporated

Inventor： Vikram GUPTA ,  Sarah Paige GIBSON ,  Jeffrey Alexander LEVIN ,  Ravindra Manohar PATWARDHAN ,  Avijit CHAKRABORTY ,  William Howard CONSTABLE ,  William Richard BELL, II

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/04

Abstract: A method for managing synapse plasticity in a neural network includes converting a first set of synapses from a plastic synapse type to a fixed synapse type. The method may also include converting a second set of synapses from the fixed synapse type to the plastic synapse type.

Abstract translation: 用于管理神经网络中的突触可塑性的方法包括将第一组突触从塑性突触类型转换为固定的突触型。 该方法还可以包括将第二组突触从固定突触型转换为塑性突触型。