Adaptive system for broadband multisignal discrimination in a channel
with reverberation
    1.
    发明授权
    Adaptive system for broadband multisignal discrimination in a channel with reverberation 失效
    用于具有混响的频道中的宽带多信号辨别的自适应系统

    公开(公告)号:US5383164A

    公开(公告)日:1995-01-17

    申请号:US74940

    申请日:1993-06-10

    摘要: A system for separating mixed signal sources by processing a received signal through the combination of a beamforming network and an adaptive Herault-Jutten network. The conventional Herault-Jutten network is useful for separating independent signals that have been linearly mixed, but cannot separate a mixture of several independent signals in free field conditions because of the propagation time delays between sources and sensors. The system of this invention combines planar beamforming techniques with a conventional HJ network to adaptively distinguish among signals having delays introduced by the propagation medium. A new sensor filter scheme is introduced to eliminate beamforming variation with frequency over the band of interest. The resulting system has application to adaptive interferer rejection and to acoustic and cellular communications receivers.

    摘要翻译: 一种用于通过波束成形网络和自适应Hérault-Jutten网络的组合处理接收信号来分离混合信号源的系统。 常规的Hérault-Jutten网络对于分离已经线性混合的独立信号是有用的,但是由于源和传感器之间的传播时间延迟,在自由场条件下不能分离几个独立信号的混合。 本发明的系统将平面波束形成技术与常规HJ网络相结合,以自适应地区分由传播介质引入的延迟的信号。 引入了一种新的传感器滤波器方案,以消除在感兴趣的频带上的频率的波束成形变化。 所得到的系统具有适用于自适应干扰源抑制和声学和蜂窝通信接收机的应用。

    Maximal-aperture reflecting objective
    3.
    发明申请
    Maximal-aperture reflecting objective 失效
    最大光圈反射目标

    公开(公告)号:US20070153368A1

    公开(公告)日:2007-07-05

    申请号:US11542634

    申请日:2006-10-02

    IPC分类号: G02B21/00

    摘要: Objectives and other optical assemblies include a reflective surface that is truncated at or near a focus based on a curvature of the reflective surface. A specimen is situated at or near the focus of the reflective surface, so that the reflective surface captures and collimates optical radiation emitted from the specimen. The reflective surface can be defined on an optical substrate along with a lens surface, so that an illumination flux is focused on the specimen by the lens surface, and a secondary light flux produced in response to the illumination flux is captured and collimated by the reflective surface.

    摘要翻译: 目标和其它光学组件包括基于反射表面的曲率在焦点处或焦点附近被截短的反射表面。 样本位于或靠近反射表面的焦点,使得反射表面捕获并准直从样本发射的光辐射。 反射表面可以与透镜表面一起限定在光学基底上,使得照射光束通过透镜表面聚焦在样本上,并且响应于照射光束产生的次级光束被反射 表面。

    Automated detection of sleep and waking states
    4.
    发明申请
    Automated detection of sleep and waking states 有权
    自动检测睡眠和醒来状态

    公开(公告)号:US20070016095A1

    公开(公告)日:2007-01-18

    申请号:US11431425

    申请日:2006-05-09

    IPC分类号: A61B5/04

    摘要: Determining low power frequency range information from spectral data. Raw signal data can be adjusted to increase dynamic range for power within low power frequency ranges as compared to higher-power frequency ranges to determine adjusted source data valuable for acquiring low power frequency range information. Low power frequency range information can be used in the analysis of a variety of raw signal data. For example, low power frequency range information within electroencephalography data for a subject from a period of sleep can be used to determine sleep states. Similarly, automated full-frequency spectral electroencephalography signal analysis can be useful for customized analysis including assessing sleep quality, detecting pathological conditions, and determining the effect of medication on sleep states.

    摘要翻译: 从频谱数据确定低功率频率范围信息。 与较高功率频率范围相比,可以调整原始信号数据以增加低功率频率范围内的功率的动态范围,以确定用于获取低功率频率范围信息的有价值的调整的源数据。 低功率频率范围信息可用于分析各种原始信号数据。 例如,可以使用从睡眠期间的对象的脑电图数据内的低功率频率范围信息来确定睡眠状态。 类似地,自动全频谱脑电图信号分析可用于定制分析,包括评估睡眠质量,检测病理状况以及确定药物对睡眠状态的影响。

    System and method of separating signals
    5.
    发明申请
    System and method of separating signals 审中-公开
    分离信号的系统和方法

    公开(公告)号:US20050149462A1

    公开(公告)日:2005-07-07

    申请号:US10949710

    申请日:2004-09-24

    CPC分类号: G06K9/624

    摘要: A computer-implemented method and apparatus that adapts class parameters, classifies data and separates sources configured in one of multiple classes whose parameters (i.e. characteristics) are initially unknown. A mixture model is used in which the observed data is categorized into two or more mutually exclusive classes. The class parameters for each of the classes are adapted to a data set in an adaptation algorithm in which class parameters including mixing matrices and bias vectors are adapted. Each data vector is assigned to one of the learned mutually exclusive classes. The adaptation and classification algorithms can be utilized in a wide variety of applications such as speech processing, image processing, medical data processing, satellite data processing, antenna array reception, and information retrieval systems.

    摘要翻译: 一种计算机实现的方法和装置,其适应类参数,对数据进行分类并分离在其参数(即特征)最初未知的多个类之一中配置的源。 使用混合模型,其中观察到的数据被分类为两个或更多个互斥类。 每个类的类参数适应于适配算法中的数据集,其中包括混合矩阵和偏置向量的类参数被适配。 每个数据向量被分配给学习的互斥类之一。 适应和分类算法可以用于诸如语音处理,图像处理,医疗数据处理,卫星数据处理,天线阵列接收和信息检索系统的各种应用中。

    Method and apparatus for efficiently encoding chromatic images using non-orthogonal basis functions

    公开(公告)号:US20060056711A1

    公开(公告)日:2006-03-16

    申请号:US11086802

    申请日:2005-03-21

    IPC分类号: G06K9/36

    摘要: A method and apparatus for efficiently encoding images using a set of non-orthogonal basis functions, thereby allowing reduction of file size, shorter transmission time, and improved accuracy. The non-orthogonal basis functions include homogenous color basis functions, luminance-encoding basis functions that have luminance edges and chromatic basis functions that exhibit color opponency. Some of the basis functions are non-orthogonal with respect to each other. Using these basis functions, a source vector is calculated to provide a number of coefficients, each coefficient associated with one basis function. The source vector is compressed by selecting a subset of the calculated coefficients, thereby providing an encoded vector. Because the method is highly efficient, the image data is substantially represented by a small number of coefficients. In some embodiments, the non-orthogonal basis functions include two or more classes. A wavelet approach can also be utilized.