Neural networks and approximation theory
โ Scribed by H.N. Mhaskar
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 192 KB
- Volume
- 9
- Category
- Article
- ISSN
- 0893-6080
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Let D be a set with a probability measure +, +(D)=1, and let K be a compact subset of L q (D, +), where the infimum is taken over all g n of the form g n = n i=1 a i , i , with arbitrary , i # K and a i # R. It is shown that for f # conv(K \_ (&K )), under some mild restrictions, \ n ( f, K ) C q =
Let D/R d be a compact set and let 8 be a uniformly bounded set of D ร R functions. For a given real-valued function f defined on D and a given natural number n, we are looking for a good uniform approximation to f of the form n i=1 a i , i , with , i # 8, a i # R. Two main cases are considered: (1)
Api~rosirnation of' reul fmctiom /I!, f&d~orwcrrd rwtwork.s of' thr ~rsurrl kind is sI~o~'rr to h lxr.scd 011 the fkntlwnet~tml principle of approxitnrrtion hx pip~pwisc-c,orl.sttr,lr fhctiotl.s.