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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nenadic, Z. Ghosh, B.K. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA (Nenadic, Z.) |
| Abstract | The authors discuss how an analog signal can be encoded using biophysically realistic neural networks. Such a network differs from a standard artificial neural network because of the fact that a biological cell generates spikes and information is encoded as activity of this spike generator and transmitted through a synapse between two cells. Thus, a biological neural network is a dynamic ensemble of cells that interact, perhaps to approximate a function, perform a recursive computation such as solving a differential equation, or retain a variable in its memory. The interaction between the cells is controlled by choosing a set of synaptic weights that have to be optimized in order that a portion of the network encode a suitable function. A new optimization algorithm for finding a set of optimal synaptic weights has been proposed and successfully implemented using a software program called GENESIS. The algorithm is illustrated by implementing a memory which is a simple network of cells encoding the identity function, together with a unity feedback. |
| Sponsorship | American Autom. Control Council |
| Starting Page | 257 |
| Ending Page | 262 |
| File Size | 514370 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780364953 |
| ISSN | 07431619 |
| DOI | 10.1109/ACC.2001.945552 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-06-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Biology computing Neurons Artificial neural networks Cells (biology) Biological information theory Biological cells Biological neural networks Computer networks Differential equations Software algorithms |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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