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ISNN
2010
Springer
14 years 10 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He
DATE
2003
IEEE
109views Hardware» more  DATE 2003»
15 years 5 months ago
Data Space Oriented Scheduling in Embedded Systems
With the widespread use of embedded devices such as PDAs, printers, game machines, cellular telephones, achieving high performance demands an optimized operating system (OS) that ...
Mahmut T. Kandemir, Guangyu Chen, Wei Zhang 0002, ...
ENTCS
2007
111views more  ENTCS 2007»
14 years 11 months ago
Compositional State Space Reduction Using Untangled Actions
We propose a compositional technique for efficient verification of networks of parallel processes. It is based on an automatic analysis of LTSs of individual processes (using a f...
Xu Wang, Marta Z. Kwiatkowska
BC
2007
113views more  BC 2007»
14 years 12 months ago
Akaike causality in state space
We present a new approach of explaining partial causality in multivariate fMRI time series by a state space model. A given single time series can be divided into two noise-driven ...
Kin Foon Kevin Wong, Tohru Ozaki
PRL
2002
128views more  PRL 2002»
14 years 11 months ago
Dynamic flies: a new pattern recognition tool applied to stereo sequence processing
The "fly algorithm" is a fast artificial evolution-based technique devised for the exploration of parameter space in pattern recognition applications. In the application...
Jean Louchet, Maud Guyon, Marie-Jeanne Lesot, Amin...