Plausible neural network with supervised and unsupervised...

Details Plausible neural network with supervised and unsupervised... Plausible neural network with supervised and unsupervised...

2007-10-23

2007-10-23

Knight, Anthony (Department: 2121)

Data processing: artificial intelligence

Neural network

Learning task

Reexamination Certificate

active

10294773

ABSTRACT:
A plausible neural network (PLANN) is an artificial neural network with weight connection given by mutual information, which has the capability of inference and learning, and yet retains many characteristics of a biological neural network. The learning algorithm is based on statistical estimation, which is faster than the gradient decent approach currently used. The network after training becomes a fuzzy/belief network; the inference and weight are exchangeable, and as a result, knowledge extraction becomes simple. PLANN performs associative memory, supervised, semi-supervised, unsupervised learning and function/relation approximation in a single network architecture. This network architecture can easily be implemented by analog VLSI circuit design.

REFERENCES:
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patent: 2002/0010691 (2002-01-01), Chen
Eugene M. Izhikevich, “Class 1 Neural Excitability, Conventional Synapses, Weakly Connected Networks, and Mathematical Foundations of Pulse-Coupled Models”,IEEE Transactions on Neural Networks, vol. 10, No. 3, pp. 499-507 (May 1999).
Ralf Salomon, “Neural Networks in the Context of Autonomous Agents: Important Concepts Revisited”, AI Lab, Computer Science Department, University of Zürich, pp. 1-8.

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