Abstract
We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.
Highlights
There are fundamental differences between how biological neural networks and human-made computer systems perform computation
Dynamics plays a crucial role in the brain, whereas in conventional Boolean circuits the dynamics is virtually nonexistent
In this paper we reviewed our dynamics based computing, and showed how dynamics can be utilized to implement logic circuits
Summary
We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and review our simple coupled dynamics based method for computing. For the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two. Reviewed by: Miguel Cornelles Soriano, University of the Balearic Islands, Spain Rider Jaimes Reategui, Guadalajara University, Mexico
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