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21. 发明授权

US06343268B1 Estimator of independent sources from degenerate mixtures 有权
标题翻译：来自退化混合物的独立来源的估计
公开(公告)号：US06343268B1
公开(公告)日：2002-01-29
申请号：US09203115
申请日：1998-12-01
申请人： Radu Balan , Alexander Jourjine , Justinian Rosca
发明人： Radu Balan , Alexander Jourjine , Justinian Rosca
IPC分类号： G10L2102
CPC分类号： G06K9/6243 , H03H21/0012 , H03H2021/0034
摘要： A system that reconstructs independent signals from degenerate mixtures estimates independent Auto Regressive (AR) processes from their sum. The system includes an identification system and an estimator. A mixture of two signals is inputted into the system and through the identifying and filtering processes, two estimates of the original signals are outputted. The identification system includes an ARMA identifier, a computation of autocovariance coefficients, an initializer and a gradient descent system. The estimator includes filtering.
摘要翻译：从退化混合中重构独立信号的系统从它们的和估计独立的自回归（AR）过程。该系统包括识别系统和估计器。将两个信号的混合输入到系统中，并且通过识别和滤波处理，输出原始信号的两个估计。识别系统包括ARMA标识符，自协方差系数的计算，初始化器和梯度下降系统。估计器包括过滤。

22. 发明授权

US09702768B2 Noise robust time of flight estimation for acoustic pyrometry 有权
公开(公告)号：US09702768B2
公开(公告)日：2017-07-11
申请号：US13961292
申请日：2013-08-07
申请人： Heiko Claussen , Justinian Rosca , Michelle Xiaohong Yan , Upul P. DeSilva , Nancy H. Ulerich
发明人： Heiko Claussen , Justinian Rosca , Michelle Xiaohong Yan , Upul P. DeSilva , Nancy H. Ulerich
IPC分类号： G01K11/24 , G01K13/02
CPC分类号： G01K11/24 , G01K13/02 , G01K2013/024
摘要： An acoustic signal traversing a hot gas is sampled at a source and a receiver and is represented in overlapping windows that maximize useable signal content. Samples in each window are processed to represented in different sparsified bins in the frequency domain. Determining a signal delay between the source and the receiver from a summation of maximum smoothed coherence transform cross-correlation values of different data windows wherein a sparseness of a mean smoothed coherence transform cross-correlation of windows is maximized. Determining a set of delay times wherein outliers are deleted to estimate a time of flight from which a temperature of the hot gas is calculated.

23. 发明申请

US20150063411A1 NON-INTRUSIVE MEASURMENT OF HOT GAS TEMPERATURE IN A GAS TURBINE ENGINE 有权
标题翻译：燃气涡轮发动机热气温度的非调节性测量
公开(公告)号：US20150063411A1
公开(公告)日：2015-03-05
申请号：US14017386
申请日：2013-09-04
申请人： Upul P. DeSilva , Heiko Claussen , Michelle Xiaohong Yan , Justinian Rosca , Nancy H. Ulerich
发明人： Upul P. DeSilva , Heiko Claussen , Michelle Xiaohong Yan , Justinian Rosca , Nancy H. Ulerich
IPC分类号： G01M15/14 , G01K13/02 , G01H3/00 , F02C7/32
CPC分类号： G01M15/14 , F02C7/32 , F05D2260/83 , G01H3/00 , G01K11/24 , G01K13/02 , G01K2013/024
摘要： A method and apparatus for operating a gas turbine engine including determining a temperature of a working gas at a predetermined axial location within the engine. An acoustic signal is encoded with a distinct signature defined by a set of predetermined frequencies transmitted as a non-broadband signal. Acoustic signals are transmitted from an acoustic transmitter located at a predetermined axial location along the flow path of the gas turbine engine. A received signal is compared to one or more transmitted signals to identify a similarity of the received signal to a transmitted signal to identify a transmission time for the received signal. A time-of-flight is determined for the signal and the time-of-flight for the signal is processed to determine a temperature in a region of the predetermined axial location.
摘要翻译：一种用于操作燃气涡轮发动机的方法和装置，包括确定发动机内预定轴向位置处的工作气体的温度。声信号用由作为非宽带信号发送的一组预定频率定义的不同签名编码。声音信号从位于燃气涡轮发动机的流路的预定轴向位置处的声发射器发射。将接收到的信号与一个或多个发射信号进行比较，以识别接收到的信号与发射信号的相似性，以识别接收信号的传输时间。确定信号的飞行时间，并处理信号的飞行时间以确定预定轴向位置的区域中的温度。

24. 发明申请

US20140064326A1 NOISE ROBUST TIME OF FLIGHT ESTIMATION FOR ACOUSTIC PYROMETRY 有权
标题翻译：噪声估计的噪声稳定时间用于声学PYROMETRY
公开(公告)号：US20140064326A1
公开(公告)日：2014-03-06
申请号：US13961292
申请日：2013-08-07
申请人： Heiko Claussen , Justinian Rosca , Michelle xiaohong Yan , Upul P. DeSilva , Nancy H. Ulerich
发明人： Heiko Claussen , Justinian Rosca , Michelle xiaohong Yan , Upul P. DeSilva , Nancy H. Ulerich
IPC分类号： G01K11/24
CPC分类号： G01K11/24 , G01K13/02 , G01K2013/024
摘要： An acoustic signal traversing a hot gas is sampled at a source and a receiver and is represented in overlapping windows that maximize useable signal content. Samples in each window are processed to represented in different sparsified bins in the frequency domain. Determining a signal delay between the source and the receiver from a summation of maximum smoothed coherence transform cross-correlation values of different data windows wherein a sparseness of a mean smoothed coherence transform cross-correlation of windows is maximized. Determining a set of delay times wherein outliers are deleted to estimate a time of flight from which a temperature of the hot gas is calculated.
摘要翻译：在源和接收器处对穿过热气体的声信号进行采样，并且在可用信号内容最大化的重叠窗口中进行表示。处理每个窗口中的样本以在频域中的不同的稀疏箱中表示。从不同数据窗口的最大平滑相干变换相加值的总和确定源和接收器之间的信号延迟，其中窗口的平均平滑相干变换互相关的稀疏度最大化。确定一组延迟时间，其中异常值被删除以估计计算出热气体的温度的飞行时间。

25. 发明申请

US20130275128A1 CHANNEL DETECTION IN NOISE USING SINGLE CHANNEL DATA 有权
标题翻译：使用单通道数据进行通道检测
公开(公告)号：US20130275128A1
公开(公告)日：2013-10-17
申请号：US13804947
申请日：2013-03-14
申请人： Heiko Claussen , Justinian Rosca
发明人： Heiko Claussen , Justinian Rosca
IPC分类号： G10L15/20
CPC分类号： G10L15/20 , G10L17/08 , G10L25/27 , G10L25/78
摘要： Methods related to Generalized Mutual Interdependence Analysis (GMIA), a low complexity statistical method for projecting data in a subspace that captures invariant properties of the data, are implemented on a processor based system. GMIA methods are applied to the signal processing problem of voice activity detection and classification. Real-world conversational speech data are modeled to fit the GMIA assumptions. Low complexity GMIA computations extract reliable features for classification of sound under noisy conditions and operate with small amounts of data. A speaker is characterized by a slow varying or invariant channel that is learned and is tracked from single channel data by GMIA methods.
摘要翻译：与广义相互依赖关系分析（GMIA）相关的方法是在基于处理器的系统上实现的一种低复杂度统计方法，用于在捕获数据不变属性的子空间中投影数据。 GMIA方法应用于语音活动检测和分类的信号处理问题。现实世界对话语音数据被建模以适应GMIA假设。低复杂度的GMIA计算提取了可靠的特征，用于在嘈杂条件下对声音进行分类，并使用少量数据进行操作。扬声器的特征在于慢速变化或不变的通道，通过GMIA方法从单通道数据中学习并跟踪。

26. 发明授权

US08489524B2 Systems and methods for turbo on-line one-class learning 有权
标题翻译：涡轮在线一级学习的系统和方法
公开(公告)号：US08489524B2
公开(公告)日：2013-07-16
申请号：US13084692
申请日：2011-04-12
申请人： Heiko Claussen , Justinian Rosca
发明人： Heiko Claussen , Justinian Rosca
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： Methods for one-class learning using support vector machines from a plurality of data batches are provided. A first support vector machine is learned from the plurality of data batches by a processor. A new data batch is received by the processor and is classified by the first support vector machine. If a non-zero loss classification occurs a new support vector machine is trained using the first support vector machine and the new data batch only. Data batches can be discarded if they are represented by the current support vector machine or after being used for training an updated support vector machine. Weighing factors applied to update the first support vector machine depend upon a parameter which is optimized iteratively. Support vectors do not need to be recalculated. A classifier is learned in a number of stages equal to the number of data batches processed on-line.
摘要翻译：提供了使用来自多个数据批次的支持向量机的一类学习的方法。通过处理器从多个数据批中学习第一支持向量机。处理器接收到新的数据批次，并由第一支持向量机分类。如果发生非零损失分类，则仅使用第一支持向量机和新的数据批次训练新的支持向量机。如果数据批次由当前的支持向量机表示，或者在用于训练更新的支持向量机之后，则可以丢弃它们。应用于更新第一支持向量机的称重因子取决于迭代优化的参数。支持向量不需要重新计算。在与在线处理的数据批次数相等的多个阶段中学习分类器。

27. 发明授权

US08315839B2 Passive and active wireless building management system and method 有权
标题翻译：被动和主动无线楼宇管理系统及方法
公开(公告)号：US08315839B2
公开(公告)日：2012-11-20
申请号：US12553753
申请日：2009-09-03
申请人： Justinian Rosca , Osman Ahmed , Chellury R. Sastry
发明人： Justinian Rosca , Osman Ahmed , Chellury R. Sastry
IPC分类号： G06F17/50
CPC分类号： H04W16/20 , H04L12/282 , H04L12/2823 , H04L67/12 , H04L2012/2841 , H04L2012/285
摘要： A building system includes a communication network, a plurality of wireless nodes, a plurality of passive wireless devices, and a processing circuit. The plurality of wireless nodes are disposed within a building operably and are coupled to the communication network. Each of the passive wireless devices is affixed to or within an object within the building. At least some of the objects constitute fixtures within the building. Each passive wireless device contains first information regarding at least one property of the object, and is configured to communicate wirelessly to at least one of the wireless nodes using power derived from communication signals detected in the passive wireless device. The processing circuit operably is coupled to receive the first information from the wireless devices, the processing circuit configured to update a model of at least a portion of a building based at least in part on the at least one property of the objects.
摘要翻译：建筑系统包括通信网络，多个无线节点，多个无源无线设备和处理电路。多个无线节点可操作地设置在建筑物内，并且耦合到通信网络。无源无线设备中的每一个被固定到建筑物内的物体内或内部。至少一些物体构成建筑物内的固定装置。每个无源无线设备包含关于对象的至少一个属性的第一信息，并且被配置为使用从在无源无线设备中检测到的通信信号导出的功率而无线地通信到至少一个无线节点。所述处理电路可操作地被耦合以从所述无线设备接收所述第一信息，所述处理电路被配置为至少部分地基于所述对象的所述至少一个属性来更新建筑物的至少一部分的模型。

28. 发明申请

US20060256978A1 Sparse signal mixing model and application to noisy blind source separation 审中-公开
标题翻译：稀疏信号混合模型和应用于噪声盲源分离
公开(公告)号：US20060256978A1
公开(公告)日：2006-11-16
申请号：US11126579
申请日：2005-05-11
申请人： Radu Balan , Justinian Rosca , Christian Borss
发明人： Radu Balan , Justinian Rosca , Christian Borss
IPC分类号： H04B15/00
CPC分类号： G06K9/6245
摘要： A computer-implemented method for blind-source separation includes capturing a mixed source signal by two or more sensors, transforming the mixed source signal from a time domain into a frequency domain, and estimating a mixing parameter of the mixed source signal. The method further includes determining a plurality of parameters of a source signal in the mixed source signal, separating the source signal from the mixed source signal under a sparsity constraint, transforming a separated source signal from the frequency domain into the time domain, and outputting the separated source signal.
摘要翻译：用于盲源分离的计算机实现的方法包括通过两个或更多个传感器捕获混合源信号，将混合源信号从时域转换成频域，以及估计混合源信号的混合参数。该方法还包括确定混合源信号中的源信号的多个参数，在稀疏约束下将源信号与混合源信号分离，将分离的源信号从频域变换为时域，并输出分离源信号。

29. 发明授权

US07110944B2 Method and apparatus for noise filtering 失效
标题翻译：用于噪声滤波的方法和装置
公开(公告)号：US07110944B2
公开(公告)日：2006-09-19
申请号：US11191105
申请日：2005-07-27
申请人： Radu Victor Balan , Justinian Rosca
发明人： Radu Victor Balan , Justinian Rosca
IPC分类号： G10L21/02
CPC分类号： G10L21/0208 , H04R3/005
摘要： A method of filtering noise from a mixed sound signal to obtain a filtered target signal, includes inputting the mixed signal through a plurality of sensors into a plurality of channels, separately Fourier transforming each the mixed signal into the frequency domain, computing a signal short-time spectral amplitude |Ŝ| from the transformed signals, computing a signal short-time spectral complex exponential ei arg(S) from said transformed signals, where arg(S) is the phase of the target signal in the frequency domain, computing said target signal S in the frequency domain from said spectral amplitude and said complex exponential, and computing a spectral power matrix and using the spectral power matrix to compute the spectral amplitude and the spectral complex exponential.
摘要翻译：一种从混合声音信号中滤除噪声以获得滤波的目标信号的方法，包括通过多个传感器将混合信号输入多个信道，将混合信号中的每一个分别进行傅里叶变换到频域，时间谱振幅| S | 从变换的信号中，从所述变换的信号计算信号短时频谱复指数e（S），其中arg（S）是频域中的目标信号的相位，计算从所述频谱幅度和所述复指数的频域中的所述目标信号S，并计算频谱功率矩阵并使用频谱功率矩阵来计算频谱幅度和频谱复数指数。

30. 发明授权

US06868365B2 Optimal ratio estimator for multisensor systems 失效
标题翻译：多传感器系统的最优比率估计器
公开(公告)号：US06868365B2
公开(公告)日：2005-03-15
申请号：US10435206
申请日：2003-05-09
申请人： Radu Victor Balan , Justinian Rosca
发明人： Radu Victor Balan , Justinian Rosca
IPC分类号： G06K9/00 , G06K9/62 , G06F15/17
CPC分类号： G06K9/6245
摘要： A signal processing technique can be effectively used for source separation, signal enhancement, and noise reduction when using a twin microphone system. The class of stochastic signals for which ratio-estimates can be computed from histograms is defined. This class fits real-world signals of interest such as voice signals. Theoretical computation in closed form of the optimal estimator for this class of signals is disclosed. Two practical implementation solutions are disclosed, as is a practical solution to exploit an echoic environment model. Furthermore, two novel techniques for signal demixing are presented. The application of the optimal estimator and the suboptimal estimator to the case of more than two channels is disclosed.
摘要翻译：当使用双麦克风系统时，信号处理技术可以有效地用于源分离，信号增强和降噪。定义可以从直方图计算比率估计的随机信号类。这个类适合现实世界的信号，如语音信号。公开了这类信号的最优估计器的封闭形式的理论计算。公开了两个实际的实现解决方案，作为利用回波环境模型的实际解决方案。此外，提出了两种用于信号分类的新颖技术。公布了最佳估计器和次优估计器在多于两个通道情况下的应用。

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