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1. 发明授权

US06581153B1 Integrated circuit 有权
标题翻译：集成电路
公开(公告)号：US06581153B1
公开(公告)日：2003-06-17
申请号：US09292959
申请日：1999-04-16
申请人： Hans Jürgen Matt , Dieter Kopp , Michael Trompf , Stefan Späth
发明人： Hans Jürgen Matt , Dieter Kopp , Michael Trompf , Stefan Späth
IPC分类号： G06F1516
CPC分类号： G06F15/7857
摘要： An integrated circuit contains a processor (DSP) for the processing of data, at least two modules (M1, M2, M3) for the processing of data packets selected by the processor according to differing operation regulations, and a router (ROUTER) which is connected to all modules (M1, M2, M3) and to the processor (DSP) for the purpose of controlling the data traffic between the processor (DSP) and the modules (M1, M2, M3). The router is suited to receive from the processor (DSP) data packets and associated instructions, to execute special operations for individual data packets which can be executed by the modules (M1, M2, M3) in specified sequence, to coordinate autonomously the control of the sequences, to transfer the data packets to the appropriate modules (M1, M2, M3), and to transfer the data packets after they have been processed according to the specified instructions to the processor (DSP).
摘要翻译：集成电路包含用于处理数据的处理器（DSP），至少两个模块（M1，M2，M3），用于根据不同的操作规则处理由处理器选择的数据包;以及路由器（ROUTER）连接到所有模块（M1，M2，M3）和处理器（DSP），以便控制处理器（DSP）和模块（M1，M2，M3）之间的数据流量。路由器适合于从处理器（DSP）数据包和相关联的指令接收，以便按照规定的顺序对模块（M1，M2，M3）执行的各个数据包执行特殊操作，以自主地协调控制将数据分组传送到适当的模块（M1，M2，M3）的序列，并且在数据分组根据指定的指令被处理之后将数据分组传送到处理器（DSP）。

2. 发明授权

US5949367A Device and method for classifying objects in an environmentally adaptive manner 失效
标题翻译：以环境适应的方式对对象进行分类的装置和方法
公开(公告)号：US5949367A
公开(公告)日：1999-09-07
申请号：US23781
申请日：1998-02-13
申请人： Michael Trompf , Hans Jurgen Matt , Dieter Baums , Gebhard Thierer
发明人： Michael Trompf , Hans Jurgen Matt , Dieter Baums , Gebhard Thierer
IPC分类号： G01S7/285 , G01S7/40 , G01S7/41 , G01S13/50 , G06K9/66
CPC分类号： G06K9/6267 , G01S7/417
摘要： Neural networks are used to classify objects automatically by means of Doppler-broadened radar echo signals. The classification device KK contains a neural network (NET, NET2) which has an input layer (IL) of input nodes (IN1, . . . , IN57) for features (M) of the Doppler-broadened radar echo signals, and an output layer (OL) of output nodes (ON1, ON2, ON3) for predetermined classes to which the objects can be allocated. The neural network (NET, NET2) is adapted to the external conditions prevailing at the time of the classification operation. The adaptation takes place either via accessible input nodes (ZN1, ZN2) into which control information (SI) can be entered, and which cause the neural network (NET) to adapt to one or to several external influence factors, or via a selection device (SEL) which, from the parameters (P1, . . . , P4) of several neural networks stored in a memory (MEM), which are trained with training data under respectively different conditions of external influence factors, selects the one most similar to the prevailing conditions.
摘要翻译：神经网络用于通过多普勒扩展的雷达回波信号自动对物体进行分类。分类装置KK包含神经网络（NET，NET2），其具有用于多普勒扩展雷达回波信号的特征（M）的输入节点（IN1，...，IN57）的输入层（IL）和输出输出节点（ON1，ON2，ON3）的层（OL），用于可以分配对象的预定类别。神经网络（NET，NET2）适应分类操作时的外部条件。适应通过可以输入控制信息（SI）的可访问输入节点（ZN1，ZN2）进行，并且使得神经网络（NET）适应于一个或多个外部影响因素，或者经由选择设备（SEL），其从存储在存储器（MEM）中的几个神经网络的参数（P1，...，P4）分别在不同的外部影响因素的条件下训练训练数据，选择最相似的现行条件。

3. 发明授权

US5758022A Method and apparatus for improved speech recognition from stress-induced pronunciation variations with a neural network utilizing non-linear imaging characteristics 失效
标题翻译：用于利用非线性成像特征的神经网络来改善来自应力引起的发音变化的语音识别的方法和装置
公开(公告)号：US5758022A
公开(公告)日：1998-05-26
申请号：US271128
申请日：1994-07-06
申请人： Michael Trompf , Heidi Hackbarth
发明人： Michael Trompf , Heidi Hackbarth
IPC分类号： G06F15/18 , G06N3/00 , G10L15/02 , G10L15/08 , G10L15/12 , G10L15/16 , G10L15/20 , G10L5/06
CPC分类号： G10L15/20 , G10L15/16
摘要： Speech recognition of Lombard-induced speech at a high rate of recognition is shown using a neural network (NN) utilizing nonlinear imaging characteristics. In a training phase, systematic parameter changes of Lombard-induced speech are trained to a neural network. In a speech recognition phase, imaging of Lombard-induced speech patterns to Lombard-free speech patterns takes place through the trained parameter changes.
摘要翻译：使用神经网络（NN）利用非线性成像特征来显示在高识别率下的伦巴底诱发语音的语音识别。在训练阶段，对神经网络训练Lombard诱导语音的系统参数变化。在语音识别阶段，Lombard诱导的语音模式对无Lombard的语音模式的成像通过训练的参数变化进行。

4. 发明授权

US06320918B1 Procedure for reducing interference in the transmission of an electrical communication signal 失效
标题翻译：降低电通信信号传输干扰的步骤
公开(公告)号：US06320918B1
公开(公告)日：2001-11-20
申请号：US09133830
申请日：1998-08-13
申请人： Michael Walker , Hans Jürgen Matt , Michael Trompf
发明人： Michael Walker , Hans Jürgen Matt , Michael Trompf
IPC分类号： H03D104
CPC分类号： G10L21/0208 , H04L25/03019
摘要： Through crosstalk on lines, interference from current transmission lines or line echoes, the useable signal is superimposed by different interference signals. The task is to find a procedure for reducing interference which, compared to the current state of the art, can be achieved with a smaller amount of computing input and is suited to both the reduction of quasi steady-state and non-steady interference. In this, the interference of a received signal is classified with regards to characteristics in the time range as a click, crackle, rumble or noise interference signal. The time range in which the interference occurs is marked. Depending on the interference type, interference blanking and/or an interpolation of the useable signal and/or a subtraction of the interference signal from the useable signal and/or a regeneration of the useable signal is carried out.
摘要翻译：通过线路上的串扰，来自当前传输线路或线路回波的干扰，可用信号由不同的干扰信号叠加。任务是找到一种减少干扰的过程，与目前的现有技术相比，可以用更少量的计算输入来实现干扰，并且适用于准稳态和非稳态干扰的降低。在此，接收信号的干扰在时间范围内被分类为点击，裂纹，隆隆声或噪声干扰信号。发生干扰的时间范围被标记。根据干扰类型，执行干扰消隐和/或可用信号的内插和/或可用信号的干扰信号的减法和/或可用信号的再生。

5. 发明授权

US5583968A Noise reduction for speech recognition 失效
标题翻译：语音识别降噪
公开(公告)号：US5583968A
公开(公告)日：1996-12-10
申请号：US219219
申请日：1994-03-29
申请人： Michael Trompf
发明人： Michael Trompf
IPC分类号： G06F15/18 , G06N3/00 , G10L15/02 , G10L15/08 , G10L15/16 , G10L15/20 , G10L21/02 , G10L5/06 , G10L9/00
CPC分类号： G10L15/20
摘要： A neural network for noise reduction for speech recognition in a noisy environment uses an algorithm for automatic network generation which automatically selects a suitable signal representation. Nodes may be added to the input layer of the neural network successively, with a new node being trained by calculating and minimizing a mapping error. A squared mapping error may be formed and the mapping error may be assigned a weight dependent on the importance of the vectors. In addition, a neural network that performs neural noise reduction by reducing, in a training phase, a mapping error between noise-free vectors at an output of the neural network and noise-reduced vectors at the output of the neural network using an iterative process, has the mapping error further reduced by additional information which is selected from a suitable signal representation at the input of the neural network.
摘要翻译：用于噪声环境中语音识别的降噪神经网络使用自动选择合适信号表示的自动网络生成算法。节点可以被连续添加到神经网络的输入层，通过计算和最小化映射误差来训练新的节点。可以形成平方的映射误差，并且可以将映射误差分配给取决于向量的重要性的权重。另外，神经网络通过在训练阶段减少在神经网络的输出处的无噪声矢量与神经网络的输出处的噪声减小向量之间的映射误差来执行神经噪声降低，所述神经网络使用迭代过程，通过在神经网络的输入端从合适的信号表示中选择的附加信息进一步降低了映射误差。

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