Hierarchical Sparse Dictionary Learning (HiSDL) for Heterogeneous High-Dimensional Time Series
    351.
    发明申请
    Hierarchical Sparse Dictionary Learning (HiSDL) for Heterogeneous High-Dimensional Time Series 有权
    用于异构高维时间序列的分层稀疏词典学习(HiSDL)

    公开(公告)号:US20160012334A1

    公开(公告)日:2016-01-14

    申请号:US14794487

    申请日:2015-07-08

    Abstract: A system, method and computer program product for hierarchical sparse dictionary learning (“HiSDL”) to construct a learned dictionary regularized by an a priori over-complete dictionary, includes providing at least one a priori over-complete dictionary for regularization, performing sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary, using a processor, updating the sparse coded dictionary with regularization using at least one auxiliary variable to provide a learned dictionary, determining whether the learned dictionary converges to an input data set, and outputting the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set. The system and method includes, when the learned dictionary lacks convergence, repeating the steps of performing sparse coding, updating the sparse coded dictionary, and determining whether the learned dictionary converges to the input data set.

    Abstract translation: 一种用于分层稀疏字典学习(“HiSDL”)的系统,方法和计算机程序产品,用于构建由先验过完整字典正规化的学习字典,包括提供至少一个用于正则化的先验过完整字典,执行稀疏编码 的所述至少一个先验过完整字典以提供稀疏编码字典,使用处理器,使用至少一个辅助变量更新所述稀疏编码字典,以提供学习字典,确定所学习的辞典是否收敛到输入 数据集,并且当学习的词典收敛到输入数据集时,输出由所述至少一个先验过完整词典正规化的学习辞典。 该系统和方法包括:当学习词典缺少收敛时,重复进行稀疏编码,更新稀疏编码词典,确定学习词典是否收敛到输入数据集的步骤。

    Regionlets with shift invariant neural patterns for object detection
    353.
    发明授权
    Regionlets with shift invariant neural patterns for object detection 有权
    具有移位不变神经模式的区域对象检测

    公开(公告)号:US09202144B2

    公开(公告)日:2015-12-01

    申请号:US14517211

    申请日:2014-10-17

    CPC classification number: G06K9/66 G06K9/4628

    Abstract: Systems and methods are disclosed for detecting an object in an image by determining convolutional neural network responses on the image; mapping the responses back to their spatial locations in the image; and constructing features densely extract shift invariant activations of a convolutional neural network to produce dense features for the image.

    Abstract translation: 公开了通过确定图像上的卷积神经网络响应来检测图像中的对象的系统和方法; 将响应映射回图像中的空间位置; 并且构造特征密集地提取卷积神经网络的移位不变激活以产生图像的密集特征。

    Compiler-guided software accelerator for iterative HADOOP® jobs
    354.
    发明授权
    Compiler-guided software accelerator for iterative HADOOP® jobs 有权
    用于迭代HADOOP®作业的编译器引导软件加速器

    公开(公告)号:US09201638B2

    公开(公告)日:2015-12-01

    申请号:US13923458

    申请日:2013-06-21

    CPC classification number: G06F8/443 G06F9/52 G06F9/546

    Abstract: Various methods are provided directed to a compiler-guided software accelerator for iterative HADOOP® jobs. A method includes identifying intermediate data, generated by an iterative HADOOP® application, below a predetermined threshold size and used less than a predetermined threshold time period. The intermediate data is stored in a memory device. The method further includes minimizing input, output, and synchronization overhead for the intermediate data by selectively using at any given time any one of a Message Passing Interface and Distributed File System as a communication layer. The Message Passing Interface is co-located with the HADOOP® Distributed File System.

    Abstract translation: 针对迭代HADOOP®作业的编译器引导软件加速器提供了各种方法。 一种方法包括将迭代HADOOP应用产生的中间数据识别为低于预定阈值大小并且使用小于预定阈值时间段的中间数据。 中间数据存储在存储设备中。 该方法还包括通过在任何给定时间选择性地使用消息传递接口和分布式文件系统中的任何一个作为通信层来最小化中间数据的输入,输出和同步开销。 消息传递接口与HADOOP®分布式文件系统位于同一位置。

    Adaptive LDPC-coded multidimensional spatial-MIMO multiband generalized OFDM
    355.
    发明授权
    Adaptive LDPC-coded multidimensional spatial-MIMO multiband generalized OFDM 有权
    自适应LDPC编码多维空间MIMO多频段广义OFDM

    公开(公告)号:US09197249B2

    公开(公告)日:2015-11-24

    申请号:US13911326

    申请日:2013-06-06

    Abstract: Systems and methods of transmitting includes one or more low-density parity-check (LDPC) encoders configured to adaptively encode one or more streams of input data by adjusting error correction strength based upon channel conditions. One or more mappers are configured to map one or more encoded data streams to symbols by associating bits of the symbols to points of an optimum signal constellation design (OSCD) based on one or more encoded data streams, the OSCD being decomposed into two or more sub-constellations. A spectral multiplexer is configured to combine symbol streams for the one or more encoded data streams to provide a plurality of spectral band groups. A mode multiplexer is configured to combine spectral contents of the plurality of spectral band groups allocated to a plurality of spatial modes for transmission over a transmission medium.

    Abstract translation: 发送系统和方法包括一个或多个低密度奇偶校验(LDPC)编码器,其被配置为通过基于信道条件调整误差校正强度来自适应地编码一个或多个输入数据流。 一个或多个映射器被配置为通过将符号的位与基于一个或多个编码数据流的最佳信号星座图设计(OSCD)的点相关联来将一个或多个编码数据流映射到符号,OSCD被分解为两个或更多个 分星座。 频谱复用器被配置为组合用于一个或多个编码数据流的符号流以提供多个频谱带组。 模式多路复用器被配置为组合分配给多个空间模式的多个频谱带组的频谱内容以便在传输介质上传输。

    Robust scale estimation in real-time monocular SFM for autonomous driving
    356.
    发明授权
    Robust scale estimation in real-time monocular SFM for autonomous driving 有权
    用于自主驾驶的实时单目SFM的鲁棒尺度估计

    公开(公告)号:US09189689B2

    公开(公告)日:2015-11-17

    申请号:US14451280

    申请日:2014-08-04

    CPC classification number: G06K9/00791 G06K9/46 G06K2009/4666

    Abstract: A method for performing three-dimensional (3D) localization requiring only a single camera including capturing images from only one camera; generating a cue combination from sparse features, dense stereo and object bounding boxes; correcting for scale in monocular structure from motion (SFM) using the cue combination for estimating a ground plane; and performing localization by combining SFM, ground plane and object bounding boxes to produce a 3D object localization.

    Abstract translation: 一种用于执行三维(3D)定位的方法,其仅需要单个相机,包括仅从一个相机捕获图像; 从稀疏特征,密集的立体声和物体边界框中产生提示组合; 使用用于估计接地平面的提示组合来校正来自运动的单眼结构(SFM)中的尺度; 并通过组合SFM,地平面和对象边界框来执行定位,以产生3D对象定位。

    Sparse higher-order Markov random field
    357.
    发明授权
    Sparse higher-order Markov random field 有权
    稀疏高阶马尔可夫随机场

    公开(公告)号:US09183503B2

    公开(公告)日:2015-11-10

    申请号:US13908715

    申请日:2013-06-03

    CPC classification number: G06N5/025

    Abstract: Systems and methods are provided for identifying combinatorial feature interactions, including capturing statistical dependencies between categorical variables, with the statistical dependencies being stored in a computer readable storage medium. A model is selected based on the statistical dependencies using a neighborhood estimation strategy, with the neighborhood estimation strategy including generating sets of arbitrarily high-order feature interactions using at least one rule forest and optimizing one or more likelihood functions. A damped mean-field approach is applied to the model to obtain parameters of a Markov random field (MRF); a sparse high-order semi-restricted MRF is produced by adding a hidden layer to the MRF; indirect long-range dependencies between feature groups are modeled using the sparse high-order semi-restricted MRF; and a combinatorial dependency structure between variables is output.

    Abstract translation: 提供了用于识别组合特征交互的系统和方法,包括捕获分类变量之间的统计依赖性,并将统计依赖性存储在计算机可读存储介质中。 基于使用邻域估计策略的统计依赖性来选择模型,邻域估计策略包括使用至少一个规则林生成任意高阶特征交互的集合并且优化一个或多个似然函数。 将阻尼平均场方法应用于模型以获得马尔可夫随机场(MRF)的参数; 通过向MRF添加隐藏层来产生稀疏高阶半限制MRF; 特征组之间的间接长程依赖关系使用稀疏高阶半限制MRF进行建模; 并输出变量之间的组合依赖结构。

    Use of second battery life to reduce CO2 emissions
    358.
    发明授权
    Use of second battery life to reduce CO2 emissions 有权
    使用第二个电池寿命来减少二氧化碳排放

    公开(公告)号:US09183327B2

    公开(公告)日:2015-11-10

    申请号:US13764100

    申请日:2013-02-11

    Abstract: A method for determining use of a second life battery under load conditions to reduce CO2 emissions includes using Monte Carlo simulations to modeling uncertainties of a load profile, a renewable energy profile, and CO2 emissions rate, determining an initial state of charge SOC of the second life battery based on a Gaussian distribution for determining a rate of charging during low emission hours and discharging during high CO2 emission hours of the second life battery and storage size of the second life battery and CO2 emissions reduction.

    Abstract translation: 用于确定在负载条件下使用第二寿命电池以减少二氧化碳排放的方法包括使用蒙特卡洛模拟来建模负载曲线,可再生能源曲线和二氧化碳排放率的不确定性,确定第二寿命电池的初始充电状态SOC 基于高斯分布的寿命电池,用于在第二寿命电池的高二氧化碳排放时段和第二寿命电池的储存尺寸以及二氧化碳排放减少期间确定低排放时间期间的充电速率和放电。

    Network fragmentation measurement in an optical wavelength division multiplexing (WDM) network
    360.
    发明授权
    Network fragmentation measurement in an optical wavelength division multiplexing (WDM) network 有权
    光波分复用(WDM)网络中的网络碎片测量

    公开(公告)号:US09166723B2

    公开(公告)日:2015-10-20

    申请号:US14177654

    申请日:2014-02-11

    CPC classification number: H04J14/021 H04J14/0224 H04J14/0257 H04L45/12

    Abstract: A method implemented in a network apparatus used in a wavelength division multiplexing (WDM) optical network is disclosed. The method includes (a) finding K-shortest routes between each node pair (s, d), where s, dεV and |V|≦K, where V is a set of reconfigurable optical add-drop multiplexer (ROADM) nodes, (b) selecting unconsidered node pair (s, d), (c) selecting unconsidered route k between nodes s and d out of the K-shortest routes, (d) finding a bit map of route k by performing bit-wise logical AND operation on bit vectors of fibers along route k, (e) selecting unconsidered line rate l out of offered set L of line rates, and (f) finding a probability αls,d,k of provisioning a connection with line rate l. Other apparatuses, systems, and methods also are disclosed.

    Abstract translation: 公开了一种在波分多路复用(WDM)光网络中使用的网络装置中实现的方法。 该方法包括:(a)找到每个节点对(s,d)之间的K个最短路径,其中s,d&egr; V和| V |和nlE; K,其中V是可重配置光分插复用器(ROADM) 节点,(b)选择未考虑的节点对(s,d),(c)从K个最短路由中的节点s和d之间选择未被考虑的路由k,(d)通过逐位执行寻找路由k的位图 沿着路线k对光纤的位向量进行逻辑与运算,(e)从所提供的线路速率集合L中选择未考虑的线路速率l,以及(f)找到用线路速率l提供连接的概率αls,d,k。 还公开了其他装置,系统和方法。

Patent Agency Ranking