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ISMIS
2000
Springer

Design of Rough Neurons: Rough Set Foundation and Petri Net Model

11 years 9 months ago
Design of Rough Neurons: Rough Set Foundation and Petri Net Model
This paper introduces the design of rough neurons based on rough sets. Rough neurons instantiate approximate reasoning in assessing knowledge gleaned from input data. Each neuron constructs upper and lower approximations as an aid to classifying inputs. The particular form of rough neuron considered in this paper relies on what is known as a rough membership function in assessing the accuracy of a classification of input signals. The architecture of a rough neuron includes one or more input ports which filter inputs relative to selected bands of values and one or more output ports which produce measurements of the degree of overlap between an approximation set and a reference set of values in classifying neural stimuli. A class of Petri nets called rough Petri nets with guarded transitions is used to model a rough neuron. An application of rough neural computing is briefly considered in classifying the waveforms of power system faults. The contribution of this article is the presentati...
James F. Peters, Andrzej Skowron, Zbigniew Suraj,
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where ISMIS
Authors James F. Peters, Andrzej Skowron, Zbigniew Suraj, Liting Han, Sheela Ramanna
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