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    • 5. 发明授权
    • Armature-mounting arrangement for a hinged-armature relay
    • 铰链式电枢继电器的电枢安装方式
    • US5900791A
    • 1999-05-04
    • US754113
    • 1996-11-22
    • Wolfgang HoffmannAndre KoernerMaik Zimmer
    • Wolfgang HoffmannAndre KoernerMaik Zimmer
    • H01H50/28H01H51/22
    • H01H50/28
    • An armature-mounting arrangement for a hinged-armature relay includes a yoke (3), an armature (1) positioned at an end portion of the yoke, and an armature holding spring (2) which has at least one switching contact thereon and which is mechanically coupled to the armature. The armature holding spring is formed as one piece with a return spring (5) for the armature and also with spring hooks (4). Each of the spring hooks has a first portion (4a) lying substantially flat on an outer side of the armature and a second portion (4b) extending from the first portion about the armature and lying almost flat against an outer surface of the yoke. This armature-mounting arrangement is a particularly uncomplicated and cost effective structure and its operation is also not particularly sensitive to fabrication tolerances of the armature and the yoke.
    • 用于铰接电枢继电器的电枢安装装置包括轭(3),位于轭的端部处的电枢(1)和在其上具有至少一个开关接触的电枢保持弹簧(2) 机械地联接到电枢。 电枢保持弹簧形成为具有用于电枢的复位弹簧(5)并且还具有弹簧钩(4)的一体式。 每个弹簧钩具有在电枢的外侧上基本上平坦的第一部分(4a)和从第一部分绕电枢延伸并且几乎平坦地抵靠轭的外表面的第二部分(4b)。 该电枢安装装置是特别简单且具有成本效益的结构,其操作对电枢和磁轭的制造公差也不特别敏感。
    • 9. 发明授权
    • Method for transforming a fuzzy logic used to simulate a technical process into a neural network
    • 将用于模拟技术过程的模糊逻辑转换为神经网络的方法
    • US06456990B1
    • 2002-09-24
    • US09355710
    • 1999-11-22
    • Wolfgang HoffmannErik Schwulera
    • Wolfgang HoffmannErik Schwulera
    • G06F1518
    • G06N3/0436
    • A method for transforming a fuzzy logic system into a neural network, where, in order to simulate membership functions, sigmoid functions are linked together in such a way that, even after the optimization of the neural network, back-transformation of the neural network into a, fuzzy logic system is possible. The advantage of the method described is that a fuzzy logic system can be transformed, in particular component by component, into a neural network and the latter can then be optimized as a whole, i.e. all the components together. The possibility of back-transforming the trained neural network ultimately means that an optimized fuzzy logic system can be obtained. This advantageously makes it possible to use, in particular, standardized fuzzy system software for describing the optimized fuzzy logic system.
    • 一种将模糊逻辑系统变换为神经网络的方法,其中为了模拟隶属函数,S形函数以这样的方式链接在一起,即即使在神经网络优化之后,将神经网络反向转换成 一个模糊逻辑系统是可能的。 所描述的方法的优点在于,可以将模糊逻辑系统,特别是按组件分组转换成神经网络,然后将模糊逻辑系统作为整体进行优化,即所有组件在一起。 对训练有素的神经网络进行反向转换的可能性最终意味着可以获得优化的模糊逻辑系统。 这有利地使得可以特别地使用用于描述优化的模糊逻辑系统的标准化模糊系统软件。