Mastorocostas, Paris A.Varsamis, Dimitris N.Mastorocostas, Costas A.Hilas, Costas S.2015-06-282024-09-272015-06-282024-09-272007http://link.springer.com/chapter/10.1007/978-3-540-74695-9_13https://repository2024.ihu.gr/handle/123456789/1556This paper presents a locally recurrent globally feedforward fuzzy neural network, with internal feedback, that performs the task of separation of lung sounds, obtained from patients with pulmonary pathology. The filter is a novel generalized Takagi-Sugeno-Kang fuzzy model, where the consequent parts of the fuzzy rules are Block-Diagonal Recurrent Neural Networks. Extensive experimental results, regarding the lung sound category of squawks, are given, and a performance comparison with a series of other fuzzy and neural filters is conducted, underlining the separation capabilities of the proposed filter.9enAttribution-NonCommercial-NoDerivatives 4.0 Διεθνέςhttp://creativecommons.org/licenses/by-nc-nd/4.0/Άρθρο σε επιστημονικό συνέδριο10.1007/978-3-540-74695-9_13