Abstract
Associativity, auto-reversibility and question-answering are the three intrinsic functions to be investigated for the proposed Q’tron Neural Network (NN) model. A Q’tron NN possesses these functions due to its property of local-minima free if it is built as a known-energy system which is equipped with the proposed persistent noise-injection mechanism. The so-built Q’tron NN, as a result, will settle down if and only if it ‘feels’ feasible, i.e., the energy of its state has been low enough truly. With such a nature, the NN is able to accommodate itself ‘everywhere’ to reach a feasible state autonomously. Three examples, i.e., an associative adder, an N-queen solver, and a pattern recognizer are demonstrated in this paper to highlight the concept.
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Yue, TW., Chen, MC. (2005). Associativity, Auto-reversibility and Question-Answering on Q’tron Neural Networks. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_106
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DOI: https://doi.org/10.1007/11538059_106
Publisher Name: Springer, Berlin, Heidelberg
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