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» Neural networks: Algorithms and applications
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FOCI
2007
IEEE
16 years 1 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
TVLSI
1998
88views more  TVLSI 1998»
15 years 6 months ago
Time multiplexed color image processing based on a CNN with cell-state outputs
—A practical system approach for time-multiplexing cellular neural network (CNN) implementations suitable for processing large and complex images using small CNN arrays is presen...
Lei Wang, José Pineda de Gyvez, Edgar S&aac...
CN
2007
221views more  CN 2007»
15 years 7 months ago
Adaptive design optimization of wireless sensor networks using genetic algorithms
We present a multi-objective optimization methodology for self-organizing, adaptive wireless sensor network design and energy management, taking into consideration application-spe...
Konstantinos P. Ferentinos, Theodore A. Tsiligirid...
PPOPP
1999
ACM
15 years 11 months ago
Automatic Node Selection for High Performance Applications on Networks
A central problem in executing performance critical parallel and distributed applications on shared networks is the selection of computation nodes and communication paths for exec...
Jaspal Subhlok, Peter Lieu, Bruce Lowekamp
IJCNN
2006
IEEE
16 years 1 months 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