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IJON
2002
105views more  IJON 2002»
13 years 7 months ago
Separation of sources using simulated annealing and competitive learning
This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated a...
Carlos García Puntonet, Ali Mansour, Christ...
HYBRID
1998
Springer
13 years 11 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
TIP
1998
129views more  TIP 1998»
13 years 7 months ago
Minimax partial distortion competitive learning for optimal codebook design
— The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is h...
Ce Zhu, Lai-Man Po
IJCNN
2000
IEEE
13 years 12 months ago
Regression Analysis for Rival Penalized Competitive Learning Binary Tree
The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penaliz...
Xuequn Li, Irwin King
INFOCOM
2010
IEEE
13 years 6 months ago
Opportunistic Spectrum Access with Multiple Users: Learning under Competition
Abstract—The problem of cooperative allocation among multiple secondary users to maximize cognitive system throughput is considered. The channel availability statistics are initi...
Animashree Anandkumar, Nithin Michael, Ao Tang