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The ability to detect faults is essential to improved reliability and security of a complex control system. Parameter estimation methods, state observation schemes, statistical likelihood ratio tests, rule-based expert system reasoning, pattern recognition techniques, and artificial neural network approaches are the most common methodologies employed. The artificial neural network, through a back-propagation learning algorithm combined with fuzzy approximate reasoning for fault diagnosis, yields superior results compared to the other methods.

A typical sigmoid function is f ( y) = 1 1 + e−y (24) For a single neuron, if the result of the sigmoid function is above a built-in threshold level, the element is activated and set to a trained value. There are many different variations of ANN; for example, in this article the discussion will center on back-propagation and feedforward error back-propagation techniques, which are the most basic ones. The feedforward error back-propagation network (EBP) is composed of a number of layers of neurons, as illustrated in Fig.

12 BUILDING WIRING Characteristics of mains channels. Mains channels have to carry current and protect the environment from voltage. The few characteristics listed in Table 6 are sufficient to characterize it. Characteristics of balanced channels. The transmission capabilities of balanced cables have considerably improved during recent years. With the sophistication of transmission technologies and their sensitivity to transmission characteristics, the number of parameters to be defined for the channel has grown.

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28.Industry Applications by John G. Webster (Editor)

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