Computation at the edge of chaos: phase transitions and emergent computation
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Associative memory in a network of biological neurons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Real-time computation at the edge of chaos in recurrent neural networks
Neural Computation
Movement prediction from real-world images using a liquid state machine
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
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A novel transient computation device is presented which performs computations on time-varying input signals. The inputs perturb the device causing transients in its internal dynamics. These transients are characteristic of the inputs and are reflected in the device's output. Previous approaches to transient computation have used large reservoirs of neurons. The proposed device consists of only two neurons with nonlinear internal dynamics. Experimental evidence is given to demonstrate that this device possesses two properties required for performing computations on time-dependent signals: a separation and an approximation property. It is also shown that this device can perform noise resistant pattern recognition.