Evolving spiking wavelet-neuro-fuzzy self-learning system
Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture.
Autor*in: |
Bodyanskiy, Ye. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2014 |
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Schlagwörter: |
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Umfang: |
7 |
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Übergeordnetes Werk: |
Enthalten in: Atomic collapse in graphene quantum dots in a magnetic field - Eren, I. ELSEVIER, 2022, the official journal of the World Federation on Soft Computing (WFSC), Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:14 ; year:2014 ; pages:252-258 ; extent:7 |
Links: |
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DOI / URN: |
10.1016/j.asoc.2013.05.020 |
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ELV027957276 |
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10.1016/j.asoc.2013.05.020 doi GBVA2014007000001.pica (DE-627)ELV027957276 (ELSEVIER)S1568-4946(13)00189-0 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 530 VZ 33.00 bkl Bodyanskiy, Ye. verfasserin aut Evolving spiking wavelet-neuro-fuzzy self-learning system 2014 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. Wavelet Elsevier Fuzzy clustering. Elsevier Multilayered spiking neural network Elsevier Self-learning Elsevier Hybrid evolving system Elsevier Computational intelligence Elsevier Control systems theory Elsevier Dolotov, A. oth Vynokurova, O. oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:14 year:2014 pages:252-258 extent:7 https://doi.org/10.1016/j.asoc.2013.05.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 14 2014 252-258 7 045F 004 |
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10.1016/j.asoc.2013.05.020 doi GBVA2014007000001.pica (DE-627)ELV027957276 (ELSEVIER)S1568-4946(13)00189-0 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 530 VZ 33.00 bkl Bodyanskiy, Ye. verfasserin aut Evolving spiking wavelet-neuro-fuzzy self-learning system 2014 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. Wavelet Elsevier Fuzzy clustering. Elsevier Multilayered spiking neural network Elsevier Self-learning Elsevier Hybrid evolving system Elsevier Computational intelligence Elsevier Control systems theory Elsevier Dolotov, A. oth Vynokurova, O. oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:14 year:2014 pages:252-258 extent:7 https://doi.org/10.1016/j.asoc.2013.05.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 14 2014 252-258 7 045F 004 |
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10.1016/j.asoc.2013.05.020 doi GBVA2014007000001.pica (DE-627)ELV027957276 (ELSEVIER)S1568-4946(13)00189-0 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 530 VZ 33.00 bkl Bodyanskiy, Ye. verfasserin aut Evolving spiking wavelet-neuro-fuzzy self-learning system 2014 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. Wavelet Elsevier Fuzzy clustering. Elsevier Multilayered spiking neural network Elsevier Self-learning Elsevier Hybrid evolving system Elsevier Computational intelligence Elsevier Control systems theory Elsevier Dolotov, A. oth Vynokurova, O. oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:14 year:2014 pages:252-258 extent:7 https://doi.org/10.1016/j.asoc.2013.05.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 14 2014 252-258 7 045F 004 |
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10.1016/j.asoc.2013.05.020 doi GBVA2014007000001.pica (DE-627)ELV027957276 (ELSEVIER)S1568-4946(13)00189-0 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 530 VZ 33.00 bkl Bodyanskiy, Ye. verfasserin aut Evolving spiking wavelet-neuro-fuzzy self-learning system 2014 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. Wavelet Elsevier Fuzzy clustering. Elsevier Multilayered spiking neural network Elsevier Self-learning Elsevier Hybrid evolving system Elsevier Computational intelligence Elsevier Control systems theory Elsevier Dolotov, A. oth Vynokurova, O. oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:14 year:2014 pages:252-258 extent:7 https://doi.org/10.1016/j.asoc.2013.05.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 14 2014 252-258 7 045F 004 |
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Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. |
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Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. |
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Highlights • Evolving system based on self-learning fuzzy spiking neural network is proposed. • The adaptive wavelet activation-membership functions usage is extended. • Complex clusters detection capability is achieved via evolving architecture. |
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