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» Learning Mappings with Neural Network
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ESANN
2003
15 years 6 months ago
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
Jianyu Li, Siwei Luo, Yingjian Qi
156
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ECAL
2007
Springer
15 years 9 months ago
Genotype Reuse More Important than Genotype Size in Evolvability of Embodied Neural Networks
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
Chad W. Seys, Randall D. Beer
ISCAS
1994
IEEE
104views Hardware» more  ISCAS 1994»
15 years 9 months ago
Stereo Correspondence with Discrete-Time Cellular Neural Networks
In this paper, we propose a new approach of solving the stereopsis problem with a discrete-time cellular neural network(DTCNN) where each node has connectionsonly with its local n...
Sungjun Park, Seung-Jai Min, Soo-Ik Chae
HVEI
2010
15 years 3 months ago
No-reference image quality assessment based on localized gradient statistics: application to JPEG and JPEG2000
This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...
Hantao Liu, Judith Redi, Hani Alers, Rodolfo Zunin...
ISNN
2007
Springer
15 years 11 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan