Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jia-Fei Wu"'
Publikováno v:
2016 IEEE Region 10 Conference (TENCON).
This paper proposes a general robust active noise control (RANC) framework for removing power line interference (PLI) from the Electroencephalogram (EEG) signals when both reference and primary signals are contaminated by spike noise. It is obtained
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 3:248-262
This paper proposes a distributed architecture for high definition multiview video surveillance system. It adopts a modular design where single view/stereo intelligent internet protocol (IP)-based video surveillance cameras are connected to a front-e
Publikováno v:
International Journal of Heat and Mass Transfer. 55:7803-7811
A closed wet cooling tower (CWCT) can be regarded as a cooling tower with the packing replaced by a bank of tubes. The heat and mass transfer in CWCT has been little investigated under supersaturated condition. The governing equations for heat and ma
Publikováno v:
TENCON 2015 - 2015 IEEE Region 10 Conference.
This paper presents an effective image structure classification method, which was recently proposed for selecting the key parameter of non-local kernel regression (NLKR) namely the kernel bandwidth. Meanwhile, to overcome the problem of intensive com
Autor:
Jia-Fei Wu, C. Chan
Publikováno v:
IEEE TENCON'90: 1990 IEEE Region 10 Conference on Computer and Communication Systems. Conference Proceedings.
Based on the principle of maximizing the likelihood of proper classification of training samples, an algorithm is proposed to train the artificial neural pattern density estimator (parallel distributed processing (PDP) network) introduced by the auth
Autor:
C. Chan, Jia-Fei Wu
Publikováno v:
IEEE TENCON'90: 1990 IEEE Region 10 Conference on Computer and Communication Systems. Conference Proceedings.
Based on the assumption that most probability densities in real life can be approximated by a mixture of Gaussian densities, the authors propose a set of algorithms for training a multilayered perceptron as a parallel distributed processing network (