Using the hermite regression formula to design a neural architecture with automatic learning of the "hidden" activation functions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1792 LNAI, Issue , 2000, Pages 226-237

  Gaglio, S ^a   Pilato, G ^a   Sorbello, F ^a   Vassallo, G ^b  

^a UNIVERSITY OF PALERMO   (Italy)

^b Centro per la Ricerca Elettronica in Sicilia (CRES)   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL ACTIVATION; NETWORK ARCHITECTURE;

ACTIVATION FUNCTIONS; AUTOMATIC-LEARNING; FEED-FORWARD NEURAL ARCHITECTURES; GENERALIZATION CAPABILITY; NEURAL ARCHITECTURES; OPTIMIZATION ALGORITHMS; REGRESSION FORMULAS; TRADITIONAL ARCHITECTURE;

ARTIFICIAL INTELLIGENCE;

EID: 85099427108     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46238-4_20     Document Type: Conference Paper

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