"\u0158e\u0161en\u00ED neline\u00E1rn\u00EDch inverzn\u00EDch \u00FAloh je \u010Dast\u00FDm probl\u00E9mem nedestruktivn\u00EDho testov\u00E1n\u00ED materi\u00E1l\u016F a konstrukc\u00ED za \u00FA\u010Delem spolehliv\u00E9ho rozpozn\u00E1n\u00ED defekt\u016F v materi\u00E1lu. Jednou z perspektivn\u00EDch diagnostick\u00FDch metod je akustick\u00E9 emise (AE), kter\u00E1 je schopna odhalit r\u016Fst nebezpe\u010Dn\u00FDch defekt\u016F, nap\u0159. trhlin, v re\u00E1ln\u00E9m \u010Dase. V 32. kapitole jsou uvedeny dva praktick\u00E9 p\u0159\u00EDklady inverzn\u00EDch \u00FAloh p\u0159i anal\u00FDze zdroj\u016F AE - lokalizace a identifikace emisn\u00EDho zdroje. Pro srovn\u00E1n\u00ED je uveden klasick\u00FD p\u0159\u00EDstup k identifika\u010Dn\u00ED inverzn\u00ED \u00FAloze, zat\u00EDmco lokalizace zdroj\u016F a inverzn\u00ED probl\u00E9m korekce sign\u00E1lov\u00FDch parametr\u016F jsou pojedn\u00E1ny pomoc\u00ED %22soft computing%22 metod na z\u00E1klad\u011B um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED (ANN). Pro tyto \u00FA\u010Dely je uveden kr\u00E1tk\u00FD \u00FAvod do teorie ANN."@cs . "[2074467BD30B]" . . . "RIV/61388998:_____/07:00089592!RIV08-AV0-61388998" . . "Vodi\u010Dka, Josef" . "15"^^ . "Solution of nonlinear Inverse Problems (IPs) is a frequent task in nondestruktive testing of materials and structures when structual defects or imperfections must be recognized. One among the most promising ultrasonic NDT techniques is the Acoustic Emission (AE) method, which can reveal a dangerous defect ( e.g.,cracks) growth in realtime. Two practical IP examples of AE source analysis are presented in this chapter: AE source location and identification. As a comparison, a classical approach to the identification IP is shown, whereas the source location and AE signal parameter correction IPs are treated by the use of the soft computing method based on Artificial Neural Networks (ANNs). A short introduction to the ANN approach is presented for that purpose."@en . . . . . "Inverse Problem Solution in Acoustic Emission Source Analysis: Classical and Artificial Neural Network Approaches" . "P(GA201/04/2102), P(GA205/03/0071), Z(AV0Z20760514)" . "Springer-Verlag" . "Solution of nonlinear Inverse Problems (IPs) is a frequent task in nondestruktive testing of materials and structures when structual defects or imperfections must be recognized. One among the most promising ultrasonic NDT techniques is the Acoustic Emission (AE) method, which can reveal a dangerous defect ( e.g.,cracks) growth in realtime. Two practical IP examples of AE source analysis are presented in this chapter: AE source location and identification. As a comparison, a classical approach to the identification IP is shown, whereas the source location and AE signal parameter correction IPs are treated by the use of the soft computing method based on Artificial Neural Networks (ANNs). A short introduction to the ANN approach is presented for that purpose." . . "427433" . . "Chlada, Milan" . . "Universality of Nonclassical Nonlinearity" . "Inverse Problem Solution in Acoustic Emission Source Analysis: Classical and Artificial Neural Network Approaches"@en . . . "P\u0159evorovsk\u00FD, Zden\u011Bk" . "Inverse Problem Solution in Acoustic Emission Source Analysis: Classical and Artificial Neural Network Approaches" . . "Torino" . . "\u0158e\u0161en\u00ED inversn\u00EDch probl\u00E9m\u016F p\u0159i anal\u00FDze zdroj\u016F akustick\u00E9 emise. Klasick\u00FD p\u0159\u00EDstup a \u0159e\u0161en\u00ED pomoc\u00ED um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED"@cs . . . "RIV/61388998:_____/07:00089592" . "515;529" . "0-387-33860-8" . "\u0158e\u0161en\u00ED inversn\u00EDch probl\u00E9m\u016F p\u0159i anal\u00FDze zdroj\u016F akustick\u00E9 emise. Klasick\u00FD p\u0159\u00EDstup a \u0159e\u0161en\u00ED pomoc\u00ED um\u011Bl\u00FDch neuronov\u00FDch s\u00EDt\u00ED"@cs . . "acoustic emission; artificial neural networks; inverse problems"@en . "3"^^ . "Inverse Problem Solution in Acoustic Emission Source Analysis: Classical and Artificial Neural Network Approaches"@en . "3"^^ . . . .