Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Olli Simula"'
Publikováno v:
Neurocomputing. 73:1919-1922
Publikováno v:
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks, Institute of Electrical and Electronics Engineers, 2009, 21 (1), pp.158-162. ⟨10.1109/TNN.2009.2036259⟩
IEEE Transactions on Neural Networks, Institute of Electrical and Electronics Engineers, 2009, 21 (1), pp.158-162
IEEE Transactions on Neural Networks, Institute of Electrical and Electronics Engineers, 2009, 21 (1), pp.158-162. ⟨10.1109/TNN.2009.2036259⟩
IEEE Transactions on Neural Networks, Institute of Electrical and Electronics Engineers, 2009, 21 (1), pp.158-162
International audience; In this brief, the optimally pruned extreme learning machine (OP-ELM) methodology is presented. It is based on the original extreme learning machine (ELM) algorithm with additional steps to make it more robust and generic. The
Autor:
Elia Liitiäinen, Amaury Lendasse, Annikki Perkiö, Satu-Pia Reinikainen, Kari Aaljoki, Roberto Baratti, Olli Simula, Francesco Corona
Publikováno v:
Journal of Chemometrics. 22:610-620
In this work, we investigated the possibility to perform wavelength selection by exploiting the metric structure of the spectrophotoscopic measurements. The topologically preserving representation of the data is performed using the self-organizing ma
Publikováno v:
IEEE Transactions on Wireless Communications. 4:930-942
The operation and maintenance of the third generation (3G) mobile networks will be challenging. These networks will be strongly service driven, and this approach differs significantly from the traditional speech dominated in the second generation (2G
Autor:
Yrjö Neuvo, Olli Simula
Publikováno v:
IFIP Advances in Information and Communication Technology
4th History of Nordic Computing (HiNC4)
4th History of Nordic Computing (HiNC4), Aug 2014, Copenhagen, Denmark. pp.367-378, ⟨10.1007/978-3-319-17145-6_37⟩
IFIP Advances in Information and Communication Technology ISBN: 9783319171449
4th History of Nordic Computing (HiNC4)
4th History of Nordic Computing (HiNC4), Aug 2014, Copenhagen, Denmark. pp.367-378, ⟨10.1007/978-3-319-17145-6_37⟩
IFIP Advances in Information and Communication Technology ISBN: 9783319171449
Part 9: IT Technology; International audience; In the 1970s research and teaching of digital signal processing was started in several universities in Scandinavia. Special emphasis in the research was on digital filter structures implementable on emer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dcf7301d2d14b4af8e2cc2b5fc498846
https://hal.inria.fr/hal-01301430
https://hal.inria.fr/hal-01301430
Autor:
Jukka Rantanen, Jouko Yliruusi, Sampsa Laine, Osmo Antikainen, Jukka-Pekka Mannermaa, Olli Simula
Publikováno v:
Journal of Pharmaceutical and Biomedical Analysis. 24:343-352
The degree of the instrumentation of pharmaceutical unit operations has increased. This instrumentation provides information of the state of the process and can be used for both process control and research. However, on-line process data is usually m
Publikováno v:
Integrated Computer-Aided Engineering. 6:3-14
The Self-Organizing Map (SOM) is a powerful neural network method for analysis and visualization of high-dimensional data. It maps nonlinear statistical dependencies between high-dimensional measurement data into simple geometric rela- tionships on a
Publikováno v:
Neurocomputing. 21:159-171
Neural receiver structures have been developed for adaptive discrete-signal detection in telecommunication applications. Neural networks combined with conventional equalizers improve the performance especially in compensating for nonlinear distortion
Publikováno v:
Advances in Computational Intelligence ISBN: 9783642386787
IWANN (1)
IWANN (1)
We consider the Extreme Learning Machine model for accurate regression estimation and the related problem of selecting the appropriate number of neurons for the model. Selection strategies that choose "the best" model from a set of candidate network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0d0aa05ddd15855f3642b2ee0809cd4
https://doi.org/10.1007/978-3-642-38679-4_41
https://doi.org/10.1007/978-3-642-38679-4_41
Autor:
Guilherme A. Barreto, Olli Simula, Amaury Lendasse, Amauri H. Souza Júnior, Yoan Miche, Francesco Corona
Publikováno v:
Advances in Computational Intelligence ISBN: 9783642386787
IWANN (1)
IWANN (1)
In this work, a novel supervised learning method, the Minimal Learning Machine (MLM), is proposed. Learning a MLM consists in reconstructing the mapping existing between input and output distance matrices and then estimating the response from the geo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7254ce06dc21a65b444c4912f2964887
https://doi.org/10.1007/978-3-642-38679-4_40
https://doi.org/10.1007/978-3-642-38679-4_40