Artificial Neural Systems: Principle and Practice

Artificial Neural Systems: Principle and Practice

Indexed in: EBSCO, Ulrich's Periodicals Directory

An intelligent system is one which exhibits characteristics including, but not limited to, learning, adaptation, and problem-solving. Artificial Neural Network (ANN) Systems are intelligent systems ...
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Emerging Networks

Pp. 198-216 (19)

Pierre Lorrentz


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.


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.


University of Kent, United Kingdom.