Superpositional Quantum Network Topologies

Details Superpositional Quantum Network Topologies Superpositional Quantum Network Topologies

2003-11-12

arxiv.org/abs/q-bio/0311016v3

International Journal of Theoretical Physics, 43, 2029-2040 (2004)

Biology

Quantitative Biology

Neurons and Cognition

10 pages, LaTeX2e

Scientific paper

10.1023/B:IJTP.0000049008.51567.

We introduce superposition-based quantum networks composed of (i) the classical perceptron model of multilayered, feedforward neural networks and (ii) the algebraic model of evolving reticular quantum structures as described in quantum gravity. The main feature of this model is moving from particular neural topologies to a quantum metastructure which embodies many differing topological patterns. Using quantum parallelism, training is possible on superpositions of different network topologies. As a result, not only classical transition functions, but also topology becomes a subject of training. The main feature of our model is that particular neural networks, with different topologies, are quantum states. We consider high-dimensional dissipative quantum structures as candidates for implementation of the model.

Affiliated with

Also associated with

No associations

Rating

Superpositional Quantum Network Topologies does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Superpositional Quantum Network Topologies, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Superpositional Quantum Network Topologies will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-337606