@article{rigatos_fuzzy_2009,
	series = {Theme: {Modeling} and {Learning}},
	title = {Fuzzy model validation using the local statistical approach},
	volume = {160},
	issn = {0165-0114},
	url = {http://www.sciencedirect.com/science/article/pii/S0165011408003412},
	doi = {10.1016/j.fss.2008.07.008},
	abstract = {The local statistical approach for fault detection and isolation is applied to fuzzy models validation. The method detects the inconsistencies between a fuzzy rule base and the modelled system. It can also identify which are the faulty parameters of the fuzzy model. The Fisher information matrix explains the detectability of changes in the parameters of the fuzzy model. Simulation tests illustrate the method's credibility.},
	number = {7},
	urldate = {2015-05-20TZ},
	journal = {Fuzzy Sets and Systems},
	author = {Rigatos, G. and Zhang, Q.},
	month = apr,
	year = {2009},
	keywords = {Detectability, Fault detection and isolation, Fisher information matrix, Fuzzy modelling, Local statistical approach},
	pages = {882--904}
}

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