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1. 发明申请

US20070260566A1 Reducing the size of a training set for classification 有权
标题翻译：减少分类训练集的大小
公开(公告)号：US20070260566A1
公开(公告)日：2007-11-08
申请号：US11403134
申请日：2006-04-11
申请人： Aleksey Urmanov , Anton Bougaev , Kenny Gross
发明人： Aleksey Urmanov , Anton Bougaev , Kenny Gross
IPC分类号： G06N3/08 , G06F15/18
CPC分类号： G06K9/6256 , G06K9/6287
摘要： A system that reduces the size of a design data set. During this design data set reduction operation, the system computes a decision boundary which separates a first group of data patterns in a training data set from a second group of data patterns in the training data set. For each data pattern in the training data set, the system determines if removing the data pattern from the training data set substantially affects the resulting decision boundary. If so, the system marks the data pattern as a key pattern. The system then removes all data patterns that are not marked as key patterns to produce a reduced training data set which represents the decision boundary.
摘要翻译：减小设计数据集大小的系统。在该设计数据集减少操作期间，系统计算将训练数据集中的第一组数据模式与训练数据集中的第二组数据模式分离的判定边界。对于训练数据集中的每个数据模式，系统确定是否从训练数据集中移除数据模式基本上影响所得的决策边界。如果是这样，系统将数据模式标记为关键模式。然后，该系统移除未标记为关键模式的所有数据模式，以产生表示决策边界的减少的训练数据集。

2. 发明申请

US20070226554A1 High-efficiency time-series archival system for telemetry signals 有权
标题翻译：遥测信号高效时间序列档案系统
公开(公告)号：US20070226554A1
公开(公告)日：2007-09-27
申请号：US11353559
申请日：2006-02-13
申请人： Jon Greaves , Keith Whisnant , Kenny Gross
发明人： Jon Greaves , Keith Whisnant , Kenny Gross
IPC分类号： G01R31/28
CPC分类号： G06F11/3452 , G06F11/3003 , G06F11/3058 , G06F11/3476 , G06K9/00536 , G06K9/6284
摘要： In one embodiment, a method and apparatus for high-efficiency time-series archiving for computer server telemetry signals is disclosed. The method includes selecting one or more telemetry signals of a plurality of telemetry signals by a sequential probability ratio test (SPRT) algorithm, the SPRT algorithm identifying the one or more telemetry signals as not consistent with normal behavior of the plurality of telemetry signals, injecting synthetic samples around the selected one or more telemetry signals to create a continuous time series telemetry sample, and analyzing the continuous time series telemetry sample to identify leading indicators of faults in the target. Other embodiments are also disclosed.
摘要翻译：在一个实施例中，公开了一种用于计算机服务器遥测信号的高效率时间序列归档的方法和装置。该方法包括通过顺序概率比测试（SPRT）算法来选择多个遥测信号中的一个或多个遥测信号，SPRT算法识别一个或多个遥测信号与多个遥测信号的正常行为不一致，注入围绕选定的一个或多个遥测信号进行合成样品，以创建连续的时间序列遥测样品，并分析连续时间序列遥测样品，以识别目标中故障的主要指标。还公开了其他实施例。

3. 发明申请

US20070179927A1 Method and apparatus for reducing execution time for parallel support vector machine computations 有权
标题翻译：用于减少并行支持向量机计算执行时间的方法和装置
公开(公告)号：US20070179927A1
公开(公告)日：2007-08-02
申请号：US11341000
申请日：2006-01-27
申请人： Kalyanaraman Vaidyanathan , Kenny Gross
发明人： Kalyanaraman Vaidyanathan , Kenny Gross
IPC分类号： G06F17/30
CPC分类号： G06K9/6269 , G06K9/00973
摘要： A system that reduces execution time of a parallel SVM application. During operation, the system partitions an input data set into chunks of data. Next, the system distributes the partitioned chunks of data across a plurality of available computing nodes and executes the parallel SVM application on the chunks of data in parallel across the plurality of available computing nodes. The system then determines if a first timeout period has been exceeded before all of the plurality of available computing nodes have finished processing their respective chunks of data. If so, the system (1) repartitions the input data set into different chunks of data; (2) redistributes the repartitioned chunks of data across some or all of the plurality of available computing nodes; and (3) executes the parallel SVM application on the repartitioned chunks of data in parallel across some or all of the available computing nodes.
摘要翻译：一种减少并行SVM应用程序执行时间的系统。在操作期间，系统将输入数据集划分成数据块。接下来，系统在多个可用计算节点之间分配分割的数据块，并且跨多个可用计算节点并行地在数据块上执行并行SVM应用。系统然后确定在所有多个可用计算节点已经完成处理其各自的数据块之前是否已经超过第一超时时段。如果是这样，系统（1）将输入数据集重新分配成不同的数据块; （2）将重新分配的数据块重新分配到多个可用计算节点的某些或全部; 和（3）在重新分配的数据块上并行地跨部分或全部可用计算节点执行并行SVM应用。

4. 发明申请

US20070179727A1 METHOD AND APPARATUS FOR REMOVING QUANTIZATION EFFECTS IN A QUANTIZED SIGNAL 有权
标题翻译：在量化信号中去除量化效应的方法和装置
公开(公告)号：US20070179727A1
公开(公告)日：2007-08-02
申请号：US11342057
申请日：2006-01-27
申请人： Kenny Gross , Ramakrishna Dhanekula , Eugenio Schuster , Gregory Cumberford
发明人： Kenny Gross , Ramakrishna Dhanekula , Eugenio Schuster , Gregory Cumberford
IPC分类号： G01R23/16 , G06F19/00
CPC分类号： H03M1/20
摘要： One embodiment of the present invention provides a system that reconstructs a high-resolution signal from a set of low-resolution quantized samples. During operation, the system receives a time series containing low-resolution quantized signal values which are sampled from the high-resolution signal. Next, the system performs a spectral analysis on the time series to obtain a frequency series for the low-resolution quantized signal values. The system next selects a subset of frequency terms from the frequency series which have the largest amplitudes. The system then reconstructs the high-resolution signal by performing an inverse spectral analysis on the subset of the frequency terms.
摘要翻译：本发明的一个实施例提供一种从一组低分辨率量化样本重构高分辨率信号的系统。在操作期间，系统接收包含从高分辨率信号中采样的低分辨率量化信号值的时间序列。接下来，系统对时间序列执行频谱分析，以获得低分辨率量化信号值的频率序列。该系统接下来从具有最大幅度的频率序列中选择频率项的子集。然后，该系统通过对频率项的子集执行反频谱分析来重构高分辨率信号。

5. 发明申请

US20070055476A1 Optimizing bandwidth and power in wireless networks of smart sensors 有权
标题翻译：优化智能传感器无线网络中的带宽和功率
公开(公告)号：US20070055476A1
公开(公告)日：2007-03-08
申请号：US11593891
申请日：2006-11-06
申请人： Keith Whisnant , Kenny Gross
发明人： Keith Whisnant , Kenny Gross
IPC分类号： G06F17/18
CPC分类号： G05B9/02 , G05B23/0221
摘要： A system that uses statistical techniques to selectively transmit data from a sensor. During operation, the system receives a sequence of quantized values from the sensor. The system then determines whether a distribution for the sequence of quantized values indicates that the sensor is observing a real event. If so, the system transmits sensor data for the real event to a receiver.
摘要翻译：一种使用统计技术从传感器选择性传输数据的系统。在操作期间，系统从传感器接收一系列量化值。然后，系统确定量化值序列的分布是否指示传感器正在观察真实事件。如果是这样，系统将传感器数据发送给接收机。

6. 发明申请

US20070214394A1 Enhancing throughput and fault-tolerance in a parallel-processing system 有权
标题翻译：提高并行处理系统的吞吐量和容错能力
公开(公告)号：US20070214394A1
公开(公告)日：2007-09-13
申请号：US11371998
申请日：2006-03-08
申请人： Kenny Gross , Alan Wood
发明人： Kenny Gross , Alan Wood
IPC分类号： G06F11/00
CPC分类号： G06F11/2041 , G06F11/1471 , G06F11/2025 , G06F11/203 , G06F11/2046
摘要： One embodiment of the present invention provides a system that enhances throughput and fault-tolerance in a parallel-processing system. During operation, the system first receives a task. Next, the system partitions N computing nodes into M set-aside nodes and N-M primary computing nodes, wherein M≧1. The system then processes the task in parallel across the N-M primary computing nodes. While doing so, the system proactively monitors the health of each of the N-M primary computing nodes. If the system detects a node in the N-M primary computing nodes to be at risk of failure, the system copies the portion of the task associated with the at-risk node to a subset of the M set-aside nodes. The system then processes the portion of the task in parallel across the subset of the M set-aside nodes while the N-M primary computing nodes continue executing.
摘要翻译：本发明的一个实施例提供一种提高并行处理系统中的吞吐量和容错能力的系统。在操作过程中，系统首先接收到一个任务。接下来，系统将N个计算节点划分为M个置换节点和N-M个主要计算节点，其中M> = 1。然后，系统在N-M主计算节点上并行处理任务。在这样做的同时，系统主动监控每个N-M主计算节点的运行状况。如果系统检测到N-M主计算节点中的节点处于故障风险，则系统将与风险中节点相关联的任务的一部分复制到M个备用节点的子集。然后，在N-M主计算节点继续执行的同时，系统跨M个备用节点的子集并行地处理任务的该部分。

7. 发明申请

US20070225926A1 METHOD AND APPARATUS FOR QUANTITATIVELY DETERMINING SEVERITY OF DEGRADATION IN A SIGNAL 有权
标题翻译：定量测定信号降解严重程度的方法与装置
公开(公告)号：US20070225926A1
公开(公告)日：2007-09-27
申请号：US11389578
申请日：2006-03-23
申请人： Kenny Gross , Keith Whisnant , Gregory Cumberford
发明人： Kenny Gross , Keith Whisnant , Gregory Cumberford
IPC分类号： G06F19/00 , G06F17/40
CPC分类号： G01R31/31708
摘要： One embodiment of the present invention provides a system that determines a severity of degradation in a signal. During operation, the system receives signal values for the signal, wherein the signal values are received with a constant sampling interval. Next, for each received signal value, the system applies a Sequential Probability Ratio Test (SPRT) to the signal value. If the SPRT generates an alarm on the signal value, the system increments a cumulative counter which records a running total number of the SPRT alarms. Upon receiving each signal value, the system updates a cumulative function using a value in the cumulative counter. Next, the system determines the severity of degradation in the signal from the shape of the cumulative function.
摘要翻译：本发明的一个实施例提供一种确定信号劣化的严重性的系统。在操作期间，系统接收信号的信号值，其中以恒定采样间隔接收信号值。接下来，对于每个接收的信号值，系统对信号值应用顺序概率比测试（SPRT）。如果SPRT在信号值上产生警报，系统会增加累积计数器，该计数器记录SPRT报警的运行总数。在收到每个信号值后，系统使用累积计数器中的值更新累积函数。接下来，系统根据累积函数的形状确定信号的劣化的严重性。

8. 发明申请

US20070220340A1 Using a genetic technique to optimize a regression model used for proactive fault monitoring 有权
标题翻译：使用遗传技术优化用于主动故障监测的回归模型
公开(公告)号：US20070220340A1
公开(公告)日：2007-09-20
申请号：US11359672
申请日：2006-02-22
申请人： Keith Whisnant , Ramakrishna Dhanekula , Kenny Gross
发明人： Keith Whisnant , Ramakrishna Dhanekula , Kenny Gross
IPC分类号： G06F11/00
CPC分类号： G06F11/0751 , G06F11/0748
摘要： One embodiment of the present invention provides a system that optimizes a regression model which predicts a signal as a function of a set of available signals. During operation, the system receives training data for the set of available signals from a computer system during normal fault-free operation. The system also receives an objective function which can be used to evaluate how well a regression model predicts the signal. Next, the system initializes a pool of candidate regression models which includes at least two candidate regression models, wherein each candidate regression model in the pool includes a subset of the set of available signals. The system then optimizes the regression model by iteratively: (1) selecting two regression models U and V from the pool of candidate regression models, wherein regression models U and V best predict the signal based on the training data and the objective function; (2) using a genetic technique to create an offspring regression model W from U and V by combining parts of the two regression models U and V; and (3) adding W to the pool of candidate regression models.
摘要翻译：本发明的一个实施例提供了一种优化回归模型的系统，该回归模型预测作为一组可用信号的函数的信号。在运行期间，在正常无故障运行期间，系统接收来自计算机系统的一组可用信号的训练数据。该系统还接收到一个目标函数，可用于评估回归模型预测信号的良好程度。接下来，系统初始化包括至少两个候选回归模型的候选回归模型池，其中池中的每个候选回归模型包括该组可用信号的子集。该系统通过迭代优化回归模型：（1）从候选回归模型池中选择两个回归模型U和V，其中回归模型U和V根据训练数据和目标函数最佳地预测信号; （2）使用遗传技术通过组合两个回归模型U和V的部分来从U和V创建后代回归模型W; 和（3）在候选回归模型池中加入W。

9. 发明申请

US20070220298A1 Method and apparatus for providing fault-tolerance in parallel-processing systems 有权
标题翻译：用于在并行处理系统中提供容错的方法和装置
公开(公告)号：US20070220298A1
公开(公告)日：2007-09-20
申请号：US11385429
申请日：2006-03-20
申请人： Kenny Gross , Alan Wood
发明人： Kenny Gross , Alan Wood
IPC分类号： G06F11/00
CPC分类号： G06F11/3409 , G06F11/3452 , G06F2201/81
摘要： A system that provides fault tolerance in a parallel processing system. During operation, the system executes a parallel computing application in parallel across a subset of computing nodes within the parallel processing system. During this process, the system monitors telemetry signals within the parallel processing system. The system analyzes the monitored telemetry signals to determine if the probability that the parallel processing system will fail is increasing. If so, the system increases the frequency at which the parallel computing application is checkpointed, wherein a checkpoint includes the state of the parallel computing application at each computing node within the parallel processing system.
摘要翻译：在并行处理系统中提供容错的系统。在操作期间，系统在并行处理系统内的计算节点的子集上并行地并行地执行并行计算应用。在此过程中，系统监视并行处理系统内的遥测信号。系统分析监控的遥测信号，以确定并行处理系统将失败的概率是否在增加。如果是，则系统增加并行计算应用程序的检查点的频率，其中检查点包括并行处理系统内的每个计算节点处的并行计算应用的状态。

10. 发明申请

US20070183305A1 High-sensitivity detection of an anomaly in a quantized signal 有权
标题翻译：高灵敏度检测量化信号中的异常
公开(公告)号：US20070183305A1
公开(公告)日：2007-08-09
申请号：US11348655
申请日：2006-02-06
申请人： Keith Whisnant , Kenny Gross
发明人： Keith Whisnant , Kenny Gross
IPC分类号： H04J11/00
CPC分类号： G06F11/0751
摘要： One embodiment of the present invention provides a system that facilitates high-sensitivity detection of an anomaly in a signal, wherein the signal is sampled to produce a set of possible quantized signal values. During operation, the system constructs a “reference distribution” for an “occurrence frequency” of a specific quantized signal value from the set of possible quantized signal values. The system then obtains a “deviant distribution” associated with the reference distribution, wherein the deviant distribution has an offset from the reference distribution to indicate an anomaly in the signal. Next, in response to a new occurrence of the specific quantized signal value, the system updates a mean and a variance of the reference distribution for the specific quantized signal value. The system also adjusts the deviant distribution for the specific quantized signal value based on the updated mean and the updated variance of the reference distribution for the specific quantized signal value. Adjusting the deviant distribution in this way reduces the offset between the reference distribution and the deviant distribution, thereby increasing system sensitivity while subsequently detecting anomalies in the signal.
摘要翻译：本发明的一个实施例提供了一种促进对信号中的异常进行高灵敏度检测的系统，其中信号被采样以产生一组可能的量化信号值。在操作期间，系统从可能的量化信号值的集合中构建特定量化信号值的“出现频率”的“参考分布”。然后，系统获得与参考分布相关联的“偏差分布”，其中偏差分布具有与参考分布的偏移以指示信号中的异常。接下来，响应于特定量化信号值的新出现，系统更新特定量化信号值的参考分布的均值和方差。该系统还基于针对特定量化信号值的参考分布的更新的平均值和更新的方差来调整特定量化信号值的偏差分布。以这种方式调整偏差分布可减少参考分布与偏差分布之间的偏移，从而提高系统灵敏度，同时检测信号中的异常。

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