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FOCI
2007
IEEE
15 years 11 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
ICCBR
2007
Springer
15 years 11 months ago
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
Thomas Gabel, Martin Riedmiller
IJCNN
2006
IEEE
15 years 10 months ago
Effective Training Methods for Function Localization Neural Networks
— Inspired by Hebb’s cell assembly theory about how the brain worked, we have developed a function localization neural network (FLNN). The main part of a FLNN is structurally t...
Takafumi Sasakawa, Jinglu Hu, Katsunori Isono, Kot...
FCCM
1997
IEEE
129views VLSI» more  FCCM 1997»
15 years 9 months ago
The Chimaera reconfigurable functional unit
By strictly separating reconfigurable logic from their host processor, current custom computing systems suffer from a significant communication bottleneck. In this paper we descri...
Scott Hauck, Thomas W. Fry, Matthew M. Hosler, Jef...
EVOW
2006
Springer
15 years 8 months ago
The Effect of Building Block Construction on the Behavior of the GA in Dynamic Environments: A Case Study Using the Shaky Ladder
The shaky ladder hyperplane-defined functions (sl-hdf's) are a test suite utilized for exploring the behavior of the genetic algorithm (GA) in dynamic environments. We present...
William Rand, Rick L. Riolo