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Anovel spiking neural network of receptive field encoding with groups of neurons decision Article

Yong-qiang MA, Zi-ru WANG, Si-yu YU, Ba-dong CHEN, Nan-ning ZHENG, Peng-ju REN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 1,   Pages 139-150 doi: 10.1631/FITEE.1700714

Abstract: Human information processing depends mainly on billions of neurons which constitute a complex neural network, and the information is transmitted in the form of neural spikes. In this paper, we propose a spiking neural network (SNN), named MD-SNN, with three key features: (1) using receptive field to encode spike trains from images; (2) randomly selecting partial spikes as inputs for each neuron to approach the absolute refractory period of the neuron; (3) using groups of neurons to make decisions. We test MD-SNN on the MNIST data set of handwritten digits, and results demonstrate that: (1) Different sizes of receptive fields influence classification results significantly. (2) Considering the neuronal refractory period in the SNN model, increasing the number of neurons in the learning layer could greatly reduce the training time, effectively reduce the probability of over-fitting, and improve the accuracy by 8.77%. (3) Compared with other SNN methods, MD-SNN achieves a better classification; compared with the convolution neural network, MD-SNN maintains flip and rotation invariance (the accuracy can remain at 90 44% on the test set), and it is more suitable for small sample learning (the accuracy can reach 80 15% for 1000 training samples, which is 7.8 times that of CNN).

Keywords： Tempotron     Receptive field     Difference of Gaussian (DoG)     Flip invariance     Rotation invariance    

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Simulation and analysis of grinding wheel based on Gaussian mixture model

Yulun CHI, Haolin LI

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 4,   Pages 427-432 doi: 10.1007/s11465-012-0350-3

Abstract: The Gaussian mixture model (GMM) is used to transform the measured non-Gaussian field to Gaussian fields

Keywords： grinding wheel     3D topographies measurement     Gaussian mixture model     simulation    

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Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality

Xin Peng, Yang Tang, Wenli Du, Feng Qian

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 429-439 doi: 10.1007/s11705-017-1675-6

Abstract: based on modified structure analysis and globality and locality preserving (MSAGL) projection, for non-Gaussianlocality preserving projection to analyze the embedding geometrical manifold and extracting the non-Gaussian

Keywords： non-Gaussian processes     subspace projection     independent component analysis     locality preserving projection    

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Temperature difference-powered carbon nanotube bearings

Quanwen HOU, Bingyang CAO, Zengyuan GUO

Frontiers in Energy 2011, Volume 5, Issue 1,   Pages 49-52 doi: 10.1007/s11708-010-0111-0

Abstract: simulations are conducted to study the motion of carbon nanotube-based nanobearings powered by temperature differenceWhen a temperature difference exists between stator nanotubes, the rotor nanotubes acquire a higher temperatureThe thermal driving force increases with the increase in temperature difference between the stators,an increase that is nearly proportional to the temperature difference.

Keywords： temperature difference-induced motion     carbon nanotubes     nanobearing     molecular dynamics simulation    

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Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 133-136 doi: 10.1007/s11709-013-0202-1

Abstract: This article examines the capability of Gaussian process regression (GPR) for prediction of effective

Keywords： unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network    

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Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 3,   Pages 276-287 doi: 10.1007/s11709-013-0207-9

Abstract: This paper describes an inverse Gaussian process-based model to characterize the growth of metal-loss

Keywords： pipeline     metal-loss corrosion     inverse Gaussian process     measurement error     hierarchical Bayesian     Markov    

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operation in the presence of different random noises and uncertainty: Implementation of generalized Gaussian

Nasser L. AZAD,Ahmad MOZAFFARI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 4,   Pages 405-412 doi: 10.1007/s11465-015-0354-x

Abstract: Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of

Keywords： automotive engine     calibration     coldstart operation     Gaussian process regression machine (GPRM)     uncertainty    

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prediction method for remaining useful life of lithium-ion batteries based on a neural network and Gaussian

Frontiers in Energy doi: 10.1007/s11708-023-0906-4

Abstract: prediction accuracy of the RUL of LIBs, a two-phase RUL early prediction method combining neural network and Gaussian

Keywords： lithium-ion batteries     RUL prediction     double exponential model     neural network     Gaussian process regression    

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Analogue Difference Balanced Function and Its Applications

Zhang Wenying,Li Shiqu

Strategic Study of CAE 2004, Volume 6, Issue 3,   Pages 45-52

Abstract:

This paper presents the concept of analogous difference of Boolean function, and call the Booleanfunction an analogue difference balanced function if whose analogous difference is balanced at any nonzero

Keywords： Bent function     perfect nonlinear function     2-radical expansion     analogue difference     analogue auto-correlationfunction     analogue difference balanced function    

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Synthesis of Intermittent-Motion Linkages with Slight Difference in Length Between Links

CHEN Xin-bo, YU Zhen

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 1,   Pages 76-79 doi: 10.1007/s11465-005-0007-6

Abstract: In this paper, (1) a new method for realizing intermittent motion, using linkages with a slight difference

Keywords： synthesis     useful     intermittent     intermittent-motion     traditional    

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Comprehensive Utilization of Temperature Difference Energy and Low-Temperature Seawater Resources

Fu Qiang, Wang Guorong, Zhou Shouwei, Zhong Lin, Zhang Li, Yu Xingyong, Yang Pu

Strategic Study of CAE 2021, Volume 23, Issue 6,   Pages 52-60 doi: 10.15302/J-SSCAE-2021.06.007

Abstract:

China has a huge amount of ocean temperature difference energy resourcesseawater to generate electricity; this can help overcome the difficulties regarding the temperature differencetechnical references and application demonstrations for the comprehensive utilization of temperature difference

Keywords： ocean temperature difference energy     low-temperature seawater resources     liquefied natural gas cold energy     comprehensive utilization     temperature difference power generation    

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Parametric control of structural responses using an optimal passive tuned mass damper under stationary Gaussian

Min-Ho CHEY, Jae-Ung KIM

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 3,   Pages 267-280 doi: 10.1007/s11709-012-0170-x

Abstract: parameters of a TMD, such as the optimal tuning frequency and optimal damping ratio, to stationary Gaussian

Keywords： tuned mass damper     parametric optimization     passive control     white noise     earthquake excitation    

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The Difference Effect of Environmental Regulation on Two Stages of Technology Innovation in China’s Manufacturing

Bao-long Yuan,Sheng-gang Ren,Xing Hu,Xuan-yu Yang

Frontiers of Engineering Management 2016, Volume 3, Issue 1,   Pages 24-29 doi: 10.15302/J-FEM-2016007

Abstract: This paper divides technological innovation into two stages: technology development and technology transfer. Then the authors use the panel data of 28 manufacturing industries during 2003–2012 to test the econometric regression model for the industry of the sub stages, which is a regulation on technological innovation in the environment. The results show that: (1) environmental regulation has a significant role in promoting China’s manufacturing technology research patent achievements, and technology into new products, and this indicated that “Porter hypothesis” in the manufacturing sector has been verified; (2) R&D and transfer expenditure have a positive impact on technological innovation. Finally, the authors put forward the corresponding policy recommendations for industry of the environmental regulation on the impact of technological innovation in phases.

Keywords： environmental regulation     technology innovation     stage difference     manufacturing    

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Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse fault

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 998-1011 doi: 10.1007/s11709-020-0621-8

Abstract: normal fault movement on a transversely crossing shallow shotcreted tunnel are investigated by 3D finite difference

Keywords： urban tunnel     sprayed concrete     reverse fault     normal fault     finite difference analysis    

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A saliency and Gaussian net model for retinal vessel segmentation Research Articles

Lan-yan XUE, Jia-wen LIN, Xin-rong CAO, Shao-hua ZHENG, Lun YU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 8,   Pages 1075-1086 doi: 10.1631/FITEE.1700404

Abstract: A novel deep learning structure called the Gaussian net (GNET) model combined with a saliency model is

Keywords： Retinal vessel segmentation     Saliency model     Gaussian net (GNET)     Feature learning    

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Title Author Date Type Operation

Anovel spiking neural network of receptive field encoding with groups of neurons decision

Yong-qiang MA, Zi-ru WANG, Si-yu YU, Ba-dong CHEN, Nan-ning ZHENG, Peng-ju REN

Journal Article

Simulation and analysis of grinding wheel based on Gaussian mixture model

Yulun CHI, Haolin LI

Journal Article

Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality

Xin Peng, Yang Tang, Wenli Du, Feng Qian

Journal Article

Temperature difference-powered carbon nanotube bearings

Quanwen HOU, Bingyang CAO, Zengyuan GUO

Journal Article

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Journal Article

Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

Journal Article

operation in the presence of different random noises and uncertainty: Implementation of generalized Gaussian

Nasser L. AZAD,Ahmad MOZAFFARI

Journal Article

prediction method for remaining useful life of lithium-ion batteries based on a neural network and Gaussian

Journal Article

Analogue Difference Balanced Function and Its Applications

Zhang Wenying,Li Shiqu

Journal Article

Synthesis of Intermittent-Motion Linkages with Slight Difference in Length Between Links

CHEN Xin-bo, YU Zhen

Journal Article

Comprehensive Utilization of Temperature Difference Energy and Low-Temperature Seawater Resources

Fu Qiang, Wang Guorong, Zhou Shouwei, Zhong Lin, Zhang Li, Yu Xingyong, Yang Pu

Journal Article

Parametric control of structural responses using an optimal passive tuned mass damper under stationary Gaussian

Min-Ho CHEY, Jae-Ung KIM

Journal Article

The Difference Effect of Environmental Regulation on Two Stages of Technology Innovation in China’s Manufacturing

Bao-long Yuan,Sheng-gang Ren,Xing Hu,Xuan-yu Yang

Journal Article

Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse fault

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

Journal Article

A saliency and Gaussian net model for retinal vessel segmentation

Lan-yan XUE, Jia-wen LIN, Xin-rong CAO, Shao-hua ZHENG, Lun YU

Journal Article