Biologically Inspired Neural Computation
Published Online: 14 DEC 2007
Copyright © 2007 by John Wiley & Sons, Inc.
Wiley Encyclopedia of Computer Science and Engineering
How to Cite
Leondopulos, S. and Micheli-Tzanakou, E. 2007. Biologically Inspired Neural Computation. Wiley Encyclopedia of Computer Science and Engineering. .
- Published Online: 14 DEC 2007
The development of intelligent machines that are capable of robust sensory perception has been an elusive task for those involved in machine intelligence. Indeed, although machines have been developed for performing on the order of 1012 floating-point operations per second, they have not been able to outperform human infants at such simple tasks as face recognition. As a result, many researchers have turned their sights to the inner workings of the biological brain itself in the hope of finding clues to the development of more robust machine perception, thus spawning the field of biologically inspired computation.
It should be noted that biologically inspired computation includes many topics that are not directly related to the function of the nervous system, such as genetic algorithms and molecular or DNA computing. However, within the context of neural networks, biologically inspired computation can be described as the development and implementation of models and algorithms that imitate the behavior of individual nerve cells (or neurons) as well as groups or nuclei of synaptically interconnected neurons.
This article discusses the relationship between the biological neuron and popular artificial neural networks that have been used in the scientific literature. In addition, applications of neural networks that are exemplary of their biological origin will be presented.
- neural networks;
- machine intelligence;