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    • 4. 发明申请
    • SYSTEM AND METHOD FOR ADAPTIVE HAPTIC EFFECTS
    • 自适应效应的系统和方法
    • WO2014209405A1
    • 2014-12-31
    • PCT/US2013/048798
    • 2013-06-29
    • INTEL CORPORATIONLIU, MinLU, MeiDING, Ke
    • LIU, MinLU, MeiDING, Ke
    • G06F3/01
    • H04M1/72569H04M19/04
    • A user device including a haptic feedback system configured to receive and process data captured by one or more sensors and determine contextual characteristics of the user device and a surrounding environment based on the captured data. The contextual characteristics may include, but are not limited to, ambient noise level and ambient light level of the surrounding environment, as well as user possession, movement and/or use and interaction with the device. The haptic feedback system is further configured to adjust haptic feedback effects of the user device based, at least in part, on the contextual characteristics of the user device and surrounding environment so as to provide an optimized haptic feedback effect to the user.
    • 一种包括触觉反馈系统的用户设备,其被配置为接收和处理由一个或多个传感器捕获的数据,并基于所捕获的数据确定所述用户设备和周围环境的上下文特征。 上下文特征可以包括但不限于周围环境的环境噪声水平和环境光水平,以及用户拥有,移动和/或与设备的使用和交互。 触觉反馈系统还被配置为至少部分地基于用户设备和周围环境的上下文特性来调整用户设备的触觉反馈效果,以便向用户提供优化的触觉反馈效果。
    • 8. 发明申请
    • HEADING ESTIMATION FOR DETERMINING A USER'S LOCATION
    • 用于确定用户位置的标题估计
    • WO2015165004A1
    • 2015-11-05
    • PCT/CN2014/076363
    • 2014-04-28
    • INTEL CORPORATIONHAN, KeDING, KeMA, JingyiHUANG, Yuhuan
    • HAN, KeDING, KeMA, JingyiHUANG, Yuhuan
    • G01C21/16
    • G01C21/16
    • Technologies for determining a user's location by a mobile computing device include detecting,based on sensed inertial characteristics of the mobile computing device,that a user of the mobile computing device has taken a physical step in a direction.The mobile computing device determines a directional heading of the mobile computing device in the direction and a variation of an orientation of the mobile computing device relative to a previous orientation of the mobile computing device at a previous physical step of the user based on the sensed inertial characteristics.The mobile computing device further applies a Kalman filter to determine a heading of the user based on the determined directional heading of the mobile computing device and the variation of the orientation and determines an estimated location of the user based on the user's determined heading,an estimated step length of the user,and a previous location of the user at the previous physical step.
    • 用于由移动计算设备确定用户位置的技术包括基于所感测到的移动计算设备的惯性特征来检测移动计算设备的用户已经沿着一个方向进行了物理步骤。移动计算设备确定方向标题 基于感测到的惯性特性,移动计算设备相对于移动计算设备在先前的物理步骤的先前方向的方向和方向的变化。移动计算设备还应用 卡尔曼滤波器,用于基于确定的移动计算设备的方向标题和方向的变化来确定用户的航向,并且基于用户确定的航向,用户的估计的步长确定用户的估计位置, 以及在之前的物理步骤中的用户的先前位置。
    • 10. 发明申请
    • NEURAL NETWORK CLASSIFICATION THROUGH DECOMPOSITION
    • 神经网络分类通过分解
    • WO2016149937A1
    • 2016-09-29
    • PCT/CN2015/075125
    • 2015-03-26
    • INTEL CORPORATIONDING, KeLUO, Chun
    • DING, KeLUO, Chun
    • G06N3/00
    • G06K9/6267G06K9/6232G06N3/063G06N3/082
    • A classification system is described which may include neural network decomposition logic ( "NND" ), which may perform classification using a neural network ( "NN" ). The NND may decompose a classification decision into multiple sub-decision spaces. The NND may perform classification using an NN that has fewer neurons than the NND utilizes for classification and/or which accepts feature vectors of a smaller size than are input into the NND. The NND may maintain multiple contexts for sub-decision spaces, and may switch between these in order to perform classification using the sub-decision spaces. The NND may combine results from the sub-decision spaces to decide a classification. By diving the decision into sub-decision spaces, the NND may provide for classification decisions using NNs that might otherwise be unsuitable for a particular classification decisions. Other embodiments may be described and/or claimed.
    • 描述了可以包括使用神经网络(“NN”)执行分类的神经网络分解逻辑(“NND”)的分类系统。 NND可以将分类决定分解成多个子决策空间。 NND可以使用具有比NND用于分类的神经元更少的NN执行分类和/或接受比输入到NND的尺寸更小的特征向量的分类。 NND可以维护用于子决策空间的多个上下文,并且可以在这些空间之间切换以便使用子决策空间来执行分类。 NND可以组合子决策空间的结果来决定分类。 通过将决策潜入潜在的决策空间,NND可以使用可能不适合特定分类决定的NN来提供分类决策。 可以描述和/或要求保护其他实施例。