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Imperfect formal neural networks with n components.
2

%I #6 Mar 17 2018 04:12:04

%S 0,0,60,15652352,18446731528483929840,

%T 1461501637330902918203677267647731623106580665344,

%U 3940200619639447921227904010014361380507973

%N Imperfect formal neural networks with n components.

%C Number of {0,1}^n to {0,1}^n vector-vector maps of which at least one component is not a formal neuron, i.e., some are not threshold gates.

%D Labos E. (1996): Long Cycles and Special Categories of Formal Neuronal Networks. Acta Biologica Hungarica, 47: 261-272.

%D Labos E. and Sette M.(1995): Long Cycle Generation by McCulloch-Pitts Networks(MCP-Nets) with Dense and Sparse Weight Matrices. Proc. of BPTM, McCulloch Memorial Conference [eds:Moreno-Diaz R. and Mira-Mira J., pp. 350-359.], MIT Press, Cambridge,MA,USA.

%D McCulloch WS and Pitts W (1943): A Logical Calculus Immanent in Nervous Activity. Bull.Math.Biophys. 5:115-133.

%F a(n)=A057156(n)-A000609(n)^n=A057156(n)-A065246(n).

%e For n = 2 the 14 threshold gates determine 14*14 = 196 neural nets each built purely from threshold gates; the remaining 2^(2*4)-14^2 = 256-196 = 60 = a(2) functions are synthesized from both neurons and non-neurons. For n = 3, 104 = A000609(3) formal neurons and 152 non-neurons gives (2^24)-A065246(3) = 15652352 = a(4) nets with at least one linearly non-separable component.

%Y Cf. A000609, A065246, A065248, A064436.

%K nonn

%O 0,3

%A _Labos Elemer_, Oct 26 2001