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» Modeling spiking neural networks
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GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
15 years 11 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
BMCBI
2010
118views more  BMCBI 2010»
15 years 6 months ago
Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry
Background: There is an increasing usage of ion mobility-mass spectrometry (IMMS) in proteomics. IMMS combines the features of ion mobility spectrometry (IMS) and mass spectrometr...
Bing Wang, Steve Valentine, Manolo Plasencia, Srir...
ECAL
2007
Springer
15 years 10 months ago
Genotype Reuse More Important than Genotype Size in Evolvability of Embodied Neural Networks
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
Chad W. Seys, Randall D. Beer
IJCNN
2006
IEEE
16 years 7 days ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...
ICANN
2010
Springer
15 years 7 months ago
Self-Organization of Steerable Topographic Mappings as Basis for Translation Invariance
One way to handle the perception of images that change in position (or size, orientation or deformation) is to invoke rapidly changing fiber projections to project images into a fi...
Junmei Zhu, Urs Bergmann, Christoph von der Malsbu...