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» Equivalent Number of Degrees of Freedom for Neural Networks
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MOBIHOC
2002
ACM
14 years 7 months ago
Topology management for sensor networks: exploiting latency and density
In wireless sensor networks, energy efficiency is crucial to achieve satisfactory network lifetime. In order to reduce the energy consumption of a node significantly, its radio ne...
Curt Schurgers, Vlasios Tsiatsis, Saurabh Ganeriwa...
GRC
2010
IEEE
13 years 8 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
EUSFLAT
2007
119views Fuzzy Logic» more  EUSFLAT 2007»
13 years 8 months ago
A New Preprocessing Approach to Preparation of Binary Patterns for FAM Neural Networks
The patterns which are presented to a Fuzzy ARTmap network should be preprocessed in such a way that the data are of appropriate clearance. In order to decrease the degree of simi...
M. Chitsaz, N. Sadati, R. Barzamini, J. Jouzdani, ...
CORR
2010
Springer
219views Education» more  CORR 2010»
13 years 5 months ago
Cooperative Algorithms for MIMO Interference Channels
Interference alignment is a transmission technique for exploiting all available degrees of freedom in the symmetric frequency- or time-selective interference channel with an arbit...
Steven W. Peters, Robert W. Heath Jr.
NECO
2000
86views more  NECO 2000»
13 years 7 months ago
A Bayesian Committee Machine
The Bayesian committee machine (BCM) is a novel approach to combining estimators which were trained on different data sets. Although the BCM can be applied to the combination of a...
Volker Tresp