SNNS

SNNS (Stuttgart Neural Network Simulator) is a software simulator for neural networks on Unix workstations developed at the Institute for Parallel and Distributed High Performance Systems (IPVR) at the University of Stuttgart. The goal of the SNNS project is to create an efficient and flexible simulation environment for research on and application of neural nets.


References in zbMATH (referenced in 12 articles )

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  1. Drałus, Grzegorz; Świątek, Jerzy: Static and dynamic complex models: comparison and application to chemical systems (2009)
  2. Aksela, Matti; Laaksonen, Jorma: Using diversity of errors for selecting members of a committee classifier (2006)
  3. Arndt, Olaf; Barth, Thomas; Freisleben, Bernd; Grauer, Manfred: Approximating a finite element model by neural network prediction for facility optimization in groundwater engineering (2005)
  4. Lacerda, Estefane; Carvalho, André C.P.L.F.; Braga, Ant^onio Pádua; Ludermir, Teresa Bernarda: Evolutionary radial basis functions for credit assessment (2005)
  5. Lacerda, Estefane; Carvalho, André C.P.L.F.; Braga, Ant^onio Pádua; Ludermir, Teresa Bernarda: Evolutionary radial basis functions for credit assessment (2005)
  6. Lacerda, Estefane; Carvalho, André C.P.L.F.; Braga, Ant^onio Pádua; Ludermir, Teresa Bernarda: Evolutionary radial basis functions for credit assessment (2005)
  7. Szczerba, Marek; Czyzewski, Andrzej: Pitch detection enhancement employing music prediction (2005)
  8. Szczerba, Marek; Czyzewski, Andrzej: Pitch detection enhancement employing music prediction (2005)
  9. Dash, Manoranjan; Liu, Huan: Consistency-based search in feature selection (2003)
  10. Dzemyda, Gintautas: Visualization of a set of parameters characterized by their correlation matrix. (2001)
  11. Thiesing, Frank M.: Analysis and prognosis of time series with neural networks (1998)
  12. Ritz, Barbara M.; Hofacker, G.Ludwig: Informational properties of neural nets performing algorithmic and logical tasks (1996)