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1.发明授权Method and apparatus for computer-supported generation of at least one artificial training data vector for a neural network 失效用于计算机支持的用于神经网络的至少一个人造训练数据矢量生成的方法和装置公开(公告)号：US06282529B1
公开(公告)日：2001-08-28
申请号：US09254298
申请日：1999-03-03
IPC分类号： G06N302
摘要： A method and apparatus for computer-supported generation of at least one artificial training data vector for a neural network is provided wherein a residual error is determined after a training of a neural network has occurred. A backward error is then determined from the residual error. Artificial training data vectors are generated from a statistical random process that is based on a statistical distribution, such that the respective backward error for an input of the neural network is taken into consideration.
摘要翻译： 提供了一种用于计算机支持地生成用于神经网络的人造训练数据向量的方法和装置，其中在发生神经网络的训练之后确定残差。 然后从剩余误差确定后向误差。 从基于统计分布的统计随机过程生成人造训练数据向量，使得考虑到神经网络的输入的相应的后向误差。
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2.发明授权ASSEMBLY OF INTERCONNECTED COMPUTING ELEMENTS, METHOD FOR COMPUTER-ASSISTED DETERMINATION OF A DYNAMICS WHICH IS THE BASE OF A DYNAMIC PROCESS, AND METHOD FOR COMPUTER-ASSISTED TRAINING OF AN ASSEMBLY OF INTERCONNECTED ELEMENTS 失效互连计算单元的组合，用于计算机辅助确定作为动态过程基础的动力学的方法以及用于计算机辅助训练组合互连元件的方法公开(公告)号：US06493691B1
公开(公告)日：2002-12-10
申请号：US09529195
申请日：2000-04-07
IPC分类号： G06N302
CPC分类号： G06N3/049
摘要： An input signal is transformed into a predetermined space. Transformation computer elements are connected to one another such that transformed signals can be taken at the transformation computer elements, whereby at least three transformed signals relate to respectively successive points in time. Composite computer elements are respectively connected to two transformation computer elements. Further, a first output computer element is provided at which an output signal that describes a system status at a point in time can be taken. The first output computer element is connected to the transformation computer elements. Further, a second output computer element is provided that is connected to the composite computer elements and given whose employment a predetermined condition can be taken into consideration when training the arrangement.
摘要翻译： 输入信号被转换成预定的空间。 变换计算机元件彼此连接，使得转换的信号可以在转换计算机元件处获取，由此至少三个变换的信号分别与时间上相连。 复合计算机元件分别连接到两个转换计算机元件。 此外，提供第一输出计算机元件，在该第一输出计算机元件处可以采用描述在某个时间点的系统状态的输出信号。 第一个输出计算机元件连接到转换计算机元件。 此外，提供第二输出计算机元件，其连接到复合计算机元件并给予其在训练该布置时可以考虑使用预定条件。
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3.发明授权Method and configuration for determining a sequence of actions for a system which comprises statuses, whereby a status transition ensues between two statuses as a result of an action 失效用于确定系统的动作序列的方法和配置，该系统包括状态，由此作为动作的结果，在两个状态之间进行状态转换公开(公告)号：US07047224B1
公开(公告)日：2006-05-16
申请号：US09787698
申请日：1999-09-08
申请人： Ralf Neuneier , Oliver Mihatsch
发明人： Ralf Neuneier , Oliver Mihatsch
IPC分类号： G06F15/18
CPC分类号： G06Q10/00
摘要： A determination of a sequence of actions is performed such that a sequence of states resulting from the sequence of actions is optimized using a prescribed optimization function. The optimization function includes a variable parameter with which it is possible to establish a risk relating to the resulting sequence of states based upon a prescribed state of the system.
摘要翻译： 执行动作序列的确定，使得使用规定的优化函数来优化由动作序列产生的状态序列。 优化功能包括可变参数，根据系统的规定状态，可以建立与所得状态相关的风险。
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公开(公告)号：US06317730B1
公开(公告)日：2001-11-13
申请号：US09194263
申请日：1998-11-23
IPC分类号： G06F1518
CPC分类号： G06N3/0436 , G06N7/046
摘要： A set of fuzzy rules (FR) is mapped onto a neural network (NN) (501). The neural network (NN) is trained (502), and weights (wi) and/or neurons (NE) of the neural network (NN) are pruned or grown (503). A new neural network (NNN) formed in this way is mapped onto a new fuzzy rule set (NFR) (504).
摘要翻译： 一组模糊规则（FR）被映射到神经网络（NN）（501）上。 神经网络（NN）被训练（502），神经网络（NN）的权重（wi）和/或神经元（NE）被修剪或生长（503）。 以这种方式形成的新神经网络（NNN）映射到新的模糊规则集（NFR）（504）。
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5.发明授权System and method for training and using interconnected computation elements to determine a dynamic response on which a dynamic process is based 失效用于训练和使用互连的计算元素以确定基于动态过程的动态响应的系统和方法公开(公告)号：US06728691B1
公开(公告)日：2004-04-27
申请号：US09914850
申请日：2001-09-04
IPC分类号： G06F1518
CPC分类号： G06N3/049
摘要： Computation elements are connected to one another with a first subsystem having a first input computation element, to which time series values, which each describe one state of a system in a first state space at a time, can be supplied. The first input computation element is connected to a first intermediate computation element, by which a state of the system can be described in a second state space at a time. In a second subsystem a second intermediate computation element, by which a state of the system can be described in the second state space at a time, is connected to a first output computation element, on which a first output signal can be tapped off. In a third subsystem a third intermediate computation element, by which a state of the system can be described in the second state space at a time, is connected to a second output computation element, on which a second output signal can be tapped off. The first subsystem, the second subsystem and the third subsystem are each connected to one another by a coupling between the intermediate computation elements. Weights, which are each associated with one connection between two intermediate computation elements are equal to one another, and weights which are each associated with a connection between an intermediate computation element and an output computation element are equal to one another.
摘要翻译： 计算元件通过具有第一输入计算元件的第一子系统相互连接，每个时间序列值描述一次在第一状态空间中的系统的一个状态。 第一输入计算元件连接到第一中间计算元件，通过该第一中间计算元件，可以一次在第二状态空间中描述系统的状态。 在第二子系统中，通过该第二中间计算元件连接到第一输出计算元件，第一中间计算元件可以一次在第二状态空间中描述系统的状态，第一输出计算元件可以在其上分离第一输出信号。 在第三子系统中，第三中间计算元件连接到第二输出计算元件，第二中间计算元件可以在第二输出计算元件上将第二输出信号分配给该第二中间计算元件。 第一子系统，第二子系统和第三子系统各自通过中间计算元件之间的耦合彼此连接。 每个与两个中间计算元件之间的一个连接相关联的权重彼此相等，并且每个与中间计算元件和输出计算元件之间的连接相关联的权重彼此相等。
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