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1. 发明授权

US06807449B1 Method for controlling and pre-setting a steelworks or parts of a steelworks 失效
标题翻译：控制和预设钢铁厂或钢厂部件的方法
公开(公告)号：US06807449B1
公开(公告)日：2004-10-19
申请号：US09463524
申请日：2000-04-19
申请人： Martin Schlang , Frank-Oliver Malisch , Otto Gramckow
发明人： Martin Schlang , Frank-Oliver Malisch , Otto Gramckow
IPC分类号： G05B1302
CPC分类号： B21B37/00 , B21B37/22 , G05B13/027 , G05B17/02
摘要： Method for controlling and preconfiguring a steelworks or parts of a steelworks, the rolling stand or the rolling mill train being controlled and preconfigured by means of a model of the rolling stand or the rolling mill train, the model having at least one neural network whose parameters are matched or adapted to the actual conditions in the rolling stand or in the rolling mill train, in particular to the properties of the strip, the rate at which the parameters are matched or adapted to the actual conditions in the rolling stand or in the rolling mill train, in particular to the properties of the strip, being varied.
摘要翻译：用于控制和预配置钢铁厂或钢厂的部件的方法，轧机机架或轧机机组通过轧机机架或轧机机组的模型进行控制和预配置，该模型具有至少一个神经网络，其参数匹配或适应于轧制机架或轧机机组中的实际情况，特别是与钢带的性能，参数匹配或适应于轧制机台中的实际情况或轧制中的速率磨坊，特别是带的属性变化。

2. 发明授权

US06745169B1 Learning process for a neural network 失效
标题翻译：神经网络的学习过程
公开(公告)号：US06745169B1
公开(公告)日：2004-06-01
申请号：US08686792
申请日：1996-07-26
申请人： Martin Schlang , Frank-Oliver Malisch , Einar Broese , Otto Gramckow
发明人： Martin Schlang , Frank-Oliver Malisch , Einar Broese , Otto Gramckow
IPC分类号： G06F1518
CPC分类号： B21B37/00 , B21B2265/12 , G05B13/027 , G06N3/08
摘要： A learning process for a neural network for open-loop or closed-loop control of an industrial process with time-variable parameters. The neural network is configured either as an open-loop or closed-loop-control network with which the process is controlled. The neural network is trained with the current process data so that it builds a model of the current process. The neural network can also be configured as a background network which is trained during operation with representative process data so that it builds an averaged model of the process over a longer period of time. After a certain learning time or upon the occurrence of an external event, the open-loop or closed-control network is replaced by the background network.
摘要翻译：用于具有时变参数的工业过程的开环或闭环控制的神经网络的学习过程。神经网络被配置为开环或闭环控制网络，过程被控制。神经网络使用当前的过程数据进行训练，从而构建当前过程的模型。神经网络还可以被配置为背景网络，其在具有代表性的过程数据的操作期间被训练，使得它在更长的时间段内构建过程的平均模型。在一定的学习时间之后或外部事件发生时，开环或闭路控制网络被后台网络所取代。

3. 发明授权

US06473658B1 Process and device for identification or pre-calculation of parameters of a time-variant industrial process 失效
标题翻译：用于识别或预先计算时变工业过程参数的过程和设备
公开(公告)号：US06473658B1
公开(公告)日：2002-10-29
申请号：US09284324
申请日：1999-06-02
申请人： Einar Bröse , Otto Gramckow , Martin Schlang , Guenter Sörgel
发明人： Einar Bröse , Otto Gramckow , Martin Schlang , Guenter Sörgel
IPC分类号： G05B1302
CPC分类号： B21B37/00
摘要： A method for identifying or predicting process parameters of an industrial process, in particular a primary-industry plant, having especially quickly varying process parameters or disturbances affecting the process, with the process parameters to be identified being determined by a process model as a function of measured values from the process, and with the process model having at least one time-invariant or one largely time-invariant process model which represents an image of the process averaged over time, and at least one time-variant process model that is adjusted to at least one time constant of a disturbance or of a variation in parameters of the process.
摘要翻译：用于识别或预测具有特别快速变化的过程参数或影响过程的干扰的工业过程，特别是一级工业设备的工艺参数的方法，其中要识别的工艺参数由作为过程模型具有至少一个时间不变或一个很大时间不变过程模型，该过程模型表示随时间平均的过程的图像，以及至少一个时变过程模型，被调整为至少一个干扰时间常数或过程参数的变化。

4. 发明授权

US5751571A Process and apparatus for determining optimum values for manipulated variables of a technical system 失效
标题翻译：用于确定技术系统的操纵变量的最佳值的过程和装置
公开(公告)号：US5751571A
公开(公告)日：1998-05-12
申请号：US578600
申请日：1996-01-04
申请人： Volker Tresp , Bernd Schurmann , Martin Schlang
发明人： Volker Tresp , Bernd Schurmann , Martin Schlang
IPC分类号： G05B13/02 , G05B13/04 , G06F15/18
CPC分类号： G05B13/042 , G05B13/027
摘要： Optimum values for manipulated variables s.sub.1, . . . ,s.sub.S of a technical system (.phi.) are determined for prescribed operational variables b.sub.1, . . . ,b.sub.B in order to optimize a prescribed target function z=g(y.sub.2. . . ,y.sub.N) of system properties y.sub.2, . . . , y.sub.N where y.sub.i =.phi..sub.i (s.sub.1, . . . ,s.sub.S,b.sub.1, . . . ,b.sub.B). Here, a set of functions f.sub.i (w.sub.1, . . . ,w.sub.W,x.sub.1, . . . ,x.sub.S=B) is used whose parameters w.sub.1, . . . ,w.sub.W are set in such a way that the functions f.sub.i model the system in such a way that the functions f.sub.i approximate the system functions .phi.i as functions of their variables x.sub.1, . . . ,x.sub.S+B in terms of an interval of prescribed magnitude; the manipulated variables s.sub.1, . . . ,s.sub.S are determined by optimizing the function g(f.sub.1 (w.sub.1, . . . ,w.sub.W,s.sub.1, . . . ,s.sub.S,b.sub.1, . . . ,b.sub.B), . . . , f.sub.N (w.sub.1, . . . ,w.sub.W,s.sub.1, . . . ,s.sub.S,b.sub.1, . . . ,b.sub.B)) at fixed values of w.sub.1, . . . ,w.sub.W and b.sub.1, . . . ,b.sub.B.
摘要翻译： PCT No.PCT / DE94 / 00762 Sec。 371日期1996年1月4日 102（e）日期1996年1月4日PCT提交1994年7月1日PCT公布。出版物WO95 / 02213 日期1995年1月19日操纵变量s1，...的最优值。。。，对于规定的操作变量b1，...确定技术系统（phi）的sS。。。，bB以便优化系统属性y2的规定目标函数z = g（y2，...，yN）。。。，yN，其中yi = phi i（s1，...，sS，b1，...，bB）。这里，使用一组函数fi（w1，...，wW，x1，...，xS = B），其参数w1，...。。。，wW被设置为使得函数fi以系统函数模拟系统，使得函数fi将系统函数phi i近似为它们的变量x1的函数。。。，xS + B以规定幅度的间隔; 操纵变量s1，。。。，sS通过优化函数g（f1（w1，...，wW，s1，...，sS，b1，...，bB），...，fN（w1，...，wW ，s1，...，sS，b1，...，bB））。。。，wW和b1，。。。，bB。

5. 发明授权

US4903304A Method and apparatus for the recognition of individually spoken words 失效
标题翻译：用于识别单独口语的方法和装置
公开(公告)号：US4903304A
公开(公告)日：1990-02-20
申请号：US262183
申请日：1988-10-20
申请人： Martin Schlang , Wolfgang Kuepper , Bernhard Kaemmerer
发明人： Martin Schlang , Wolfgang Kuepper , Bernhard Kaemmerer
IPC分类号： G10L15/00 , G10L15/02 , G10L15/08 , G10L3/00
CPC分类号： G10L25/87 , G10L15/00 , G10L25/00
摘要： A system for recognizing individually spoken words includes an acousto-electric transducer with a controllable amplifier and a high-pass filter connected to a level calculation path for calculating the level of the output signal by detecting the signal envelope and converting the envelope signal to a 1-bit digital signal to be supplied to a microprocessor. A signal analysis path is also connected to the transducer and includes a low-pass filter followed by a 1-bit analog to digital converter and a digital processing unit which supplies data units to the microprocessor. Individually spoken words are recognized and actions taken accordingly.
摘要翻译：用于识别单独口语的系统包括具有可控放大器的声电换能器和连接到电平计算路径的高通滤波器，用于通过检测信号包络并将包络信号转换为1来计算输出信号的电平位数字信号提供给微处理器。信号分析路径也连接到换能器，并且包括一个低通滤波器，随后是1位模数转换器和一个向微处理器提供数据单元的数字处理单元。单独口头的话得到承认，并采取相应的行动。

6. 发明授权

US5417211A Method for the classification of field patterns generated by electrophysiological activities 失效
标题翻译：电生理活动产生的场地分类方法
公开(公告)号：US5417211A
公开(公告)日：1995-05-23
申请号：US101043
申请日：1993-08-03
申请人： Klaus Abraham-Fuchs , Martin Schlang , Johann Uebler
发明人： Klaus Abraham-Fuchs , Martin Schlang , Johann Uebler
IPC分类号： A61B5/05 , G06F17/00 , G06K9/00
CPC分类号： G06K9/0057 , Y10S128/925 , Y10S706/924
摘要： A method for classifying field patterns generated by electrophysiological activities occurring inside the body of a living subject includes the steps of measuring field patterns arising as a result of the electrophysiological activities outside the body of the subject using a multi-channel measuring apparatus, generating feature vectors corresponding to the measured field patterns, supplying the feature vectors to an adaptive classifier, and training the adaptive classifier with training field patterns which have been generated by a localizable surrogate model of the electrophysiological activity. The method includes the further step of generating a probability value for each field pattern at an output of the adaptive classifier which indicates the probability with which each field pattern can be generated by a selected localizable surrogate model. This classification method greatly reduces the number of possible patterns which must be reviewed by a physician in order to evaluate the electrophysiological activity of the subject.
摘要翻译：用于分类由生物体内发生的电生理活动产生的场模式的方法包括以下步骤：使用多通道测量装置测量作为受试者体外的电生理活动的结果所产生的场模式，产生特征向量对应于测量的场模式，将特征向量提供给自适应分类器，以及训练具有由电生理活动的可本地化替代模型产生的训练场模式的自适应分类器。该方法包括在自适应分类器的输出处生成每个场模式的概率值的进一步步骤，该自适应分类器指示可由所选择的可本地化代理模型生成每个场模式的概率。这种分类方法大大减少了医师为了评估受试者的电生理活动必须审查的可能模式的数量。

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