By Laurene V. Fausett
Supplying unique examples of straightforward functions, this new e-book introduces using neural networks. It covers basic neural nets for trend category; trend organization; neural networks in line with pageant; adaptive-resonance idea; and extra. For pros operating with neural networks.
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Additional resources for Fundamentals of Neural Networks: Architectures, Algorithms And Applications
Example text
2n}, cS,t i Hih denote the Hamming distance between bit representations i and h. 2n}. So for the example with 2n = 8 protein types we have d ∈ {0, 1, 2, 3}, and for every protein there is one binding site type matching perfectly (N(d = 0) = 1), three binding site types with N(1) = 3, three with N(2) = 3, and only one where all bits are different (N(3) = 1). e. after the above calculations are done). Because of c) no decay rates for SFs need to be evolved and no saturation value applies, but cS,t i ∈ [0, 1].
Given the current state, the update rule determines the following state. The update rule can be an explicit table (if the number of states is finite) or, more often, a formula. 1 shows both cases for a Boolean Network with three nodes. F. Knabe: Computational GRNs: Evolvable, Self-organizing Systems, SCI 428, pp. 45–70. com 46 4 Biological Clocks and Differentiation 1 1 NXOR 3 3 t=n t=n+1 3 AND 2 3 IMPL 2 123 123 2 0 0 0 1 0 1 1 1 0 0 1 0 1 1 0 1 0 1 0 0 1 0 1 1 0 1 1 0 1 1 1 1 1 0 1 0 0 0 1 1 1 0 1 1 1 1 0 1 Fig.
7 Example gene representation. The gene 010111021101020011113 (assuming n = 3 bits, 23 = 8 protein types possible) will produce protein 7 (111) and is “off by default” (last digit before the terminating 3 is 1). It has two cis-modules, the first inhibitory (starting with 0) binding a combination of proteins 5 (101) and 6 (110), and an activatory cis-module (starting with 1) to which protein 5 (101) will bind. The last zero of the cis-module 110102 as well as the following two zeros are all ignored, they are “junk”.