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» On the weight convergence of Elman networks
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IJON
2007
184views more  IJON 2007»
13 years 7 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
TSP
2012
12 years 3 months ago
On the Rate Gap Between Multi- and Single-Cell Processing Under Opportunistic Scheduling
—Base station (BS) coordination is a key technique to handle intercell interference (ICI) in cellular networks. Nevertheless, recent work on scheduling indicates that the value o...
Hans Jørgen Bang, David Gesbert, Pål ...
CEC
2007
IEEE
14 years 1 months ago
Improving generalization capability of neural networks based on simulated annealing
— This paper presents a single-objective and a multiobjective stochastic optimization algorithms for global training of neural networks based on simulated annealing. The algorith...
Yeejin Lee, Jong-Seok Lee, Sun-Young Lee, Cheol Ho...
JPDC
2007
84views more  JPDC 2007»
13 years 7 months ago
Distributed average consensus with least-mean-square deviation
We consider a stochastic model for distributed average consensus, which arises in applications such as load balancing for parallel processors, distributed coordination of mobile a...
Lin Xiao, Stephen P. Boyd, Seung-Jean Kim
TSP
2010
13 years 2 months ago
Optimization and analysis of distributed averaging with short node memory
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
Boris N. Oreshkin, Mark Coates, Michael G. Rabbat