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Programming the Mind and Decrypting the Universe—A Bipolar Quantum-Neuro-Fuzzy Associative Memory Model for Quantum Cognition and Quantum Intelligence
The 2017 International Joint Conference on Neural Networks (IJCNN 2017) (2017)
  • Wen-Ran Zhang
Abstract
Extending a geometrical and logical unification of mind, light, and matter, a Quantum-Neuro-Fuzzy Associative Memory (QNFAM) model is proposed for equilibrium-based Quantum Cognition and Quantum Intelligence (QC&QI). It is argued that the brain is neither an electric power machine nor a digital computer, but a dynamic equilibrium of neuron ensembles of bipolar quantum agents. Thus, neuronal electrical signals are inadequate for QC&QI due their incurred loss of dynamic equilibrium information. On the other hand, it is pointed out that the illogical aspect of quantum mechanics prevents quantum computing from lending itself as an analytical paradigm for equilibrium-based QC&QI. QNFAM is proposed to bridge the gap. Equilibrium and nonequilibrium conditions of QNFAM are identified and axiomatically proved. It is illustrated that QNFAM leads to QC&QI – an equilibrium-based super symmetrical and analytical unification of logical, physical, biological, social, and mental systems for Programming the Mind and Decrypting the Universe.
Keywords
  • Energy/Information Conservation,
  • Quantum Cognition,
  • Quantum Intelligence,
  • Programming the Mind,
  • Decrypting the Universe,
  • Equilibrium-based Neuroscience,
  • Equilibrium-based Cosmology,
  • Mind-Light-Matter Unification
Disciplines
Publication Date
May, 2017
Citation Information
Wen-Ran Zhang. "Programming the Mind and Decrypting the Universe—A Bipolar Quantum-Neuro-Fuzzy Associative Memory Model for Quantum Cognition and Quantum Intelligence" The 2017 International Joint Conference on Neural Networks (IJCNN 2017) (2017)
Available at: http://works.bepress.com/wen-ran_zhang/47/