Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Spaanenburg, Lambert"'
Autor:
Grunditz, Carl-Henrik1 calle.grunditz@telia.com, Spaanenburg, Lambert1
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2004, Vol. 15 Issue 1, p29-39. 11p. 1 Black and White Photograph, 5 Diagrams, 4 Charts, 5 Graphs.
Autor:
Van Veelen, Martijn1 veelen@astron.nl, Spaanenburg, Lambert2
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2004, Vol. 15 Issue 1, p47-59. 13p. 9 Diagrams, 7 Graphs.
Autor:
Spaanenburg, Lambert
Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4cef51fdfc455540cc41c7d3ecf4576
Autor:
Malki, Suleyman, Spaanenburg, Lambert
Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient solutions. Cellular Neural Networks have this promise. This paper explores digital realizations of such computational paradigms through the case of real
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7332f63c9ec1e57921782cd33a1e981c
https://lup.lub.lu.se/record/603849
https://lup.lub.lu.se/record/603849
Autor:
vanVeelen, M, Spaanenburg, Lambert
Publikováno v:
pp 54-59 (2004)
The past decade has witnessed a marked increase in distributed system complexity. This was driven by a maturing technology that steadily decreased the number of faults. Unfortunately these fewer faults have become exponentially more costly. It become
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a370a68ac2ff3ff92e954e125c6c103a
http://lup.lub.lu.se/record/603837/file/645340
http://lup.lub.lu.se/record/603837/file/645340
Publikováno v:
14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC), 517-522
STARTPAGE=517;ENDPAGE=522;TITLE=14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
STARTPAGE=517;ENDPAGE=522;TITLE=14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
Novelty detection is based on the creation of a space with similarity metric. It is discussed that the design of a neural detector is a compromise between promptness, universatility, robustness and sensitivity. The feed-forward topology is chosen fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::bfbff9c0bed1c303bf72fca0b4ef8a1a
https://research.utwente.nl/en/publications/it-takes-a-winner-to-take-his-share(0079772a-7756-4339-b373-2abc4578cdd6).html
https://research.utwente.nl/en/publications/it-takes-a-winner-to-take-his-share(0079772a-7756-4339-b373-2abc4578cdd6).html
Publikováno v:
14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC), 447-452
STARTPAGE=447;ENDPAGE=452;TITLE=14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
STARTPAGE=447;ENDPAGE=452;TITLE=14th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
A major disadvantage of feedforward neural networks is still the difficulty to gain insight into their internal functionality. This is much less the case for, e.g., nets that are trained unsupervised, such as Kohonen’s self-organizing feature maps
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::4420e29d7f2ccc8778f531559ad1b136
https://research.utwente.nl/en/publications/translating-feedforward-neural-nets-to-somlike-maps(2da7fd09-aeb6-46cc-8b7e-4783b4a35a84).html
https://research.utwente.nl/en/publications/translating-feedforward-neural-nets-to-somlike-maps(2da7fd09-aeb6-46cc-8b7e-4783b4a35a84).html
Autor:
van der Zwaag, B.J., Slump, Cornelis H., Spaanenburg, Lambert, Palade, Vasile, Howlett, Robert J., Jain, Lakhmi
Publikováno v:
Proceedings of KES2003 vol. II, 950-957
STARTPAGE=950;ENDPAGE=957;TITLE=Proceedings of KES2003 vol. II
Lecture Notes in Computer Science ISBN: 9783540408048
KES
STARTPAGE=950;ENDPAGE=957;TITLE=Proceedings of KES2003 vol. II
Lecture Notes in Computer Science ISBN: 9783540408048
KES
This paper illustrates a novel method to analyze artificial neural networks so as to gain insight into their internal functionality. To this purpose, we will show analysis results of some feed-forward–error-back-propagation neural networks for imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6371a9c2f694858099fe486ab6903dc5
https://doi.org/10.1007/978-3-540-45226-3_130
https://doi.org/10.1007/978-3-540-45226-3_130
Publikováno v:
13th Annual Workshop on Circuits Systems and Signal Processing (ProRISC), 580-586
STARTPAGE=580;ENDPAGE=586;TITLE=13th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
STARTPAGE=580;ENDPAGE=586;TITLE=13th Annual Workshop on Circuits Systems and Signal Processing (ProRISC)
This paper illustrates a novel method to analyze artificial neural networks so as to gain insight into their internal functionality. To this purpose, the elements of a feedforward-backpropagation neural network, that has been trained to detect edges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::bef15615d275e2f330dab6af5bae6454
https://research.utwente.nl/en/publications/analysis-of-neural-networks-for-edge-detection(1176b721-0397-4197-8d8d-9a6bd756bd84).html
https://research.utwente.nl/en/publications/analysis-of-neural-networks-for-edge-detection(1176b721-0397-4197-8d8d-9a6bd756bd84).html