Artificial Neural Systems: Principle and Practice

Emerging Networks

Author(s): Pierre Lorrentz

Pp: 198-216 (19)

DOI: 10.2174/9781681080901115010012

* (Excluding Mailing and Handling)


Considering the possible availability of non-volatile memory element, chapter 10 has presented a memristive neural network in its first section. Generally, the chapter aims to present those neural systems that, at present, exist as proof of concept, some of which are undergoing industrial tests. For this reason, quantum neural networks are described in relative detail, and without losing its generality. A category of Bayesian network commonly known as Deep Belief Networks (DBN) is revisited, this time to illustrate their industrial tests. This chapter has provided some informational resources on the present state of ANNs′ development. It has also striven to bridge the gap between researches, developments, and applications.

Keywords: Amplifier, Bridge Circuit, Coupling Strength, Doublet Generator, Entanglement, Green Function, Hierarchical Bayesian Network, Kth phonon, Memristance, Probability Density, OFF-state, ON-state, Period, Polarization, Pulse, Q-dot, Schroedinger Equation, Synapses, Time-slice, Transconductance, Transistor.

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