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沈阳自动化研究所 [2]
地理科学与资源研究所 [1]
成都山地灾害与环境研... [1]
长春光学精密机械与物... [1]
数学与系统科学研究院 [1]
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OAI收割 [6]
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期刊论文 [3]
会议论文 [2]
SCI/SSCI论文 [1]
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2017 [1]
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Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network
期刊论文
OAI收割
Applied Soft Computing, 2022, 卷号: 118, 页码: 1-13
作者:
Chao, Zhen
;
Duan, Xingguang
;
Jia, Shuangfu
;
Guo, Xuejun
;
Liu H(刘浩)
  |  
收藏
  |  
浏览/下载:78/0
  |  
提交时间:2022/03/07
Discrete stationary wavelet transform
Enhanced radial basis function neural network
Medical image fusion
The Analysis for the Cargo Volume with Hybrid Discrete Wavelet Modeling
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2017, 卷号: 16, 期号: 3, 页码: 851-863
作者:
Xiao, Yi
;
Wang, Shouyang
;
Xiao, Ming
;
Xiao, Jin
;
Hu, Yi
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2018/07/30
Cargo volume analyzing
radial basis function network
discrete wavelet technique
TEI@I methodology
Study and Application of Wavelet-based Denoising Method of Seismic Effect Signals of Colluvium Accumulation Slope
期刊论文
OAI收割
Sensors & Transducers, 2014, 卷号: 177, 期号: 7, 页码: 259-264
作者:
Xie Fei
;
Dong Huang
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2016/12/05
Round motion
Topography effect
Dynamic response
Denoising
Wavelet basis function
Improved continuous wavelet analysis of variation in the dominant period of hydrological time series
SCI/SSCI论文
OAI收割
2013
作者:
Wang D.
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2014/12/24
hydrological series analysis
continuous wavelet transform
wavelet
basis function
multi-temporal scale
wavelet spectrum
period
trend
change points
maximum entropy spectral analysis
de-noising
entropy spectral-analysis
decomposition
identification
transform
threshold
model
Selective Method of Wavelet Basis Function and Application in Signal Processing of EGG
会议论文
OAI收割
Kunming, China, March 20-23, 2011
作者:
Ding W(丁伟)
;
Qin SJ(秦书嘉)
;
Miao L(缪磊)
;
Li HY(李洪谊)
;
Wang YC(王越超)
  |  
收藏
  |  
浏览/下载:61/0
  |  
提交时间:2012/06/06
Electrogastrogram
Wavelet Transform
Wavelet Basis Function
Entropy
Power Spectrum
Image compression based on contourlet and no lists SPIHT (EI CONFERENCE)
会议论文
OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者:
Zhang S.
收藏
  |  
浏览/下载:51/0
  |  
提交时间:2013/03/25
The volume of raw image data captured by the high resolution camera is extremely huge. Thus the efficient image compression method should be used to decrease the bit rate. The image compression method based on wavelet is used more widely nowadays. However
two dimensional wavelet is only the tensor product of the one dimensional wavelet whose support region of basis function is extended from interval to square. Contourlet is an image multiscale geometric analysis tool
which could represent image sparsely and has strong capability of nonlinear approximation. The basis function of contourlet is multidirectional and anisotropic. Nevertheless
contourlet is redundant. So the non-redundant Wavelet Based Contourlet Transform (WBCT) is used in this paper. The SPIHT algorithm is very efficient way to coding the significant coefficients. And the improved no lists SPIHT is more easy to implemented by hardware. Image compression method based on the combination of both wavelet based contourlet transform and no lists SPIHT coding is proposed in the paper. Experiment shows that compared to wavelet based scheme the contourlet scheme can reserve the texture of the image. For barbara test image when coding at low bit rate the PSNR can improve about 0.2dB. 2010 IEEE.