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TNN
1998
96views more  TNN 1998»
15 years 5 months ago
Noise suppressing sensor encoding and neural signal orthonormalization
In this paper we regard first the situation where parallel channels are disturbed by noise. With the goal of maximal information conservation we deduce the conditions for a transf...
Rüdiger W. Brause, M. Rippl
BVAI
2005
Springer
15 years 11 months ago
Learning Location Invariance for Object Recognition and Localization
A visual system not only needs to recognize a stimulus, it also needs to find the location of the stimulus. In this paper, we present a neural network model that is able to genera...
Gwendid T. van der Voort van der Kleij, Frank van ...
TNN
1998
146views more  TNN 1998»
15 years 5 months ago
An analytical framework for local feedforward networks
Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are refer...
S. Weaver, L. Baird, Marios M. Polycarpou
ECAL
1999
Springer
15 years 10 months ago
Evolution of Neural Controllers with Adaptive Synapses and Compact Genetic Encoding
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
Dario Floreano, Joseba Urzelai
IJCNN
2006
IEEE
16 years 8 hour ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh