Paper Info
Title
Challenge for a Real-World Information Processing by Means of Real-Time Neural Computation and Real-Conditions Simulation
Abstract
Should we consider the dimensions of natural neural computation as they are known as a result of the scientific research, we realize there is a long tomorrow before us, interested in neural computation, for the simple reason that we can only handle a relatively low number of units and connections nowadays. All along this century we have significantly improved our knowledge on natural neural nets, to realize that huge number of cells and connections and begin to understand some of the brain signals processing and the repetitive structures which support it. However, even in the most developed cases, such as the auditory pathway modelling, there is not a neural computational device which can involve a real time response and follow the facts already known or plausibly postulated on some brain processes (e.g. by McCulloch and Pitts), with the unavoidable great number of processing elements involved too, besides neither suitable models regarding those kind of real-look nets have been designed nor their corresponding real-conditions simulations have been carried out. That means there is a lack of connectionistically computable models and also reduction methods by which we can obtain a connectionistic implementation design, given the knowledge level model. Therefore, we would like to ask: what is within reach? In order to answer this question we are going to present a restricted auditory pathway modelling case, where we shall be able to see the realistic challenges we are facing up tp. By trying to propose a consistent implementation for it, based on parallel, modular, distributed and self-programming computation, we shall see the kind of methods, equipment, software and simulations required and desirable.
Year
DOI
Venue
1999
10.1007/BFb0100497
LECTURE NOTES IN COMPUTER SCIENCE
Keywords
Field
DocType
signal processing,scientific research,information processing,neural net,real time
Signal processing,Information processing,Knowledge level,Computer science,Models of neural computation,Artificial intelligence,Artificial neural network,Machine learning,Time response,Scientific method
Conference
Volume
ISSN
Citations 
1607
0302-9743
1
PageRank 
References 
Authors
0.37
7
1
Name
Order
Citations
PageRank
Juan Carlos Herrero1173.42