Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Eng Yeow Cheu"'
Publikováno v:
IEEE Transactions on Signal Processing. 56:3627-3637
A minimum mean-square error (MMSE)-based iterative soft interference cancellation (MMSE-SIC) receiver has been proposed to mitigate the interferences of the multiple-input multiple-output (MIMO) channels, with reduced complexity as compared to maximu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11ddb7eeb02856be6665475138cae1de
https://doi.org/10.1109/tsp.2008.921723
https://doi.org/10.1109/tsp.2008.921723
Publikováno v:
IJCNN
In this paper, we present a novel way of pre-training deep architectures by using the stochastic least squares autoencoder (SLSA). The SLSA is based on the combination of stochastic least squares estimation and logistic sampling. The usefulness of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::771f9f02804c667a9b08d76e5ab6944d
https://doi.org/10.1109/ijcnn.2015.7280502
https://doi.org/10.1109/ijcnn.2015.7280502
Publikováno v:
IJCNN
The hippocampus is involved with the storage and retrieval of short-term associative memories. In this paper, we propose a computationally efficient associative memory model of the hippocampus CA3 region by spiking neurons, and explores the storage o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19c26b6f77863f4fb36ae50ac3b554b6
https://doi.org/10.1109/ijcnn.2013.6706923
https://doi.org/10.1109/ijcnn.2013.6706923
Publikováno v:
IJCNN
This paper analyses traffic prediction based on a Generic Self-Evolving Takagi-Sugeno-Kang (GSETSK) fuzzy neural network. Traffic prediction is a problem that requires online adaptive systems with high accuracy performance. The proposed GSETSK framew
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::658a9f422c7b83b71baefa08e1b5c871
https://doi.org/10.1109/ijcnn.2012.6252409
https://doi.org/10.1109/ijcnn.2012.6252409
Autor:
Eng Yeow Cheu
Publikováno v:
EAIS
This paper describes a simple learning method to sequentially select recent time series values as features to model the differential trend of a time series. This method is used to solve the First International Competition on Time Series Forecasting (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae1de0e09c2be5282ec4c23a5620024b
https://doi.org/10.1109/eais.2012.6232830
https://doi.org/10.1109/eais.2012.6232830
Publikováno v:
IJCNN
Neuro-fuzzy system (NFS) has successfully been widely applied in solving problems across diverse fields, such as signal detection, fault detection, and forecasting. In recent years, many forecasting problems require the processing and learning of lar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f051f1cd6d4c6ca457e60f8e29c90fe4
https://hdl.handle.net/10356/97871
https://hdl.handle.net/10356/97871
Publikováno v:
IJCNN
The usage of online learning technique in neuro-fuzzy system (NFS) to address system variance is more prevalent in recent times. Since a lot of external factors have an effect on time-variant datasets, these datasets tend to experience changes in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::726054b10f3100c46c3913e600940fe4
https://hdl.handle.net/10356/98222
https://hdl.handle.net/10356/98222
Publikováno v:
Journal of computational neuroscience. 33(3)
Jensen et al. (Learn Memory 3(2–3):243–256, 1996b) proposed an auto-associative memory model using an integrated short-term memory (STM) and long-term memory (LTM) spiking neural network. Their model requires that distinct pyramidal cells encodin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f73b5e53756cdf49ac08c123e889a95c
https://pubmed.ncbi.nlm.nih.gov/22644788
https://pubmed.ncbi.nlm.nih.gov/22644788
Publikováno v:
FUZZ-IEEE
This paper presents an online learning-based neuro-fuzzy system called evolving Fuzzy Ensemble (eFE). The hierarchical computational structure of eFE is progressively adapted to autonomously support fuzzy data associations in accordance with neurophy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3d8447d555cdf25a3814b0ffc8c1dd8
https://doi.org/10.1109/fuzzy.2011.6007358
https://doi.org/10.1109/fuzzy.2011.6007358
Appetitive operant conditioning in Aplysia for feeding behavior via the electrical stimulation of the esophageal nerve contingently reinforces each spontaneous bite during the feeding process. This results in the acquisition of operant memory by the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b40ae6f697078954a6bdad73f56a317
http://hdl.handle.net/10220/13507
http://hdl.handle.net/10220/13507