Approximation theory and feedforward networks

Neural Networks

Volumn 4, Issue 4, 1991, Pages 511-515

  Blum, Edward K ^a   Li, Leong Kwan ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Approximation; Feedforward networks; Three layer nets; Two layer nets

Indexed keywords

COMPUTER METATHEORY--PROGRAMMING THEORY;

COMPUTATIONAL MODELS; FEEDFORWARD NETWORKS;

NEURAL NETWORKS;

EID: 0025747581     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(91)90047-9     Document Type: Article

References (12)

1. Approximation by superpositions of a sigmoidal function
2. Implications and applications of Kolmogorov's superposition theorem
3. On the approximate realization of continuous mappings by neural networks
4. Multi-layer feedforward networks are universal approximators
5. On the representation of continuous functions of several variables by superposition of continuous functions of one variable and addition
6. How neural nets work
7. An introduction to computing with neural nets
8. Representation properties of networks Kolmogorov's theorem is irrelevant
9. On the structure of continuous functions of several variables