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Description: ICA watermarking. Blind, fragile, robust
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Size: 342016 |
Author: archer |
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Description: 压缩传感，压缩感知，压缩采样，稀疏表达，稀疏表示，的入门介绍，自己精心搜集的ppt，pdf资料，助你轻松入门-compressive sening compressed sensing
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Size: 17413120 |
Author: 赵佳 |
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Description: ceemdan是对EMD EEMD的改进算法，此程序包中有子程序和测试例子，可以运行-his algorithm was presented at ICASSP 2011, Prague, Czech Republic
Plese, if you use this code in your work, please cite the paper where the
algorithm was first presented.
If you use this code, please cite:
M.E.TORRES, M.A. COLOMINAS, G. SCHLOTTHAUER, P. FLANDRIN,
"A complete Ensemble Empirical Mode decomposition with adaptive noise,"
IEEE Int. Conf. on Acoust., Speech and Signal Proc. ICASSP-11, pp. 4144-4147, Prague (CZ)
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Size: 5120 |
Author: 张力 |
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Description: This program implements the rendering framework that is used in the paper
D. De Silva, W. Fernando, and H. Kodikaraarachchi,
“A NEW MODE SELECTION TECHNIQUE FOR CODING DEPTH MAPS OF 3D VIDEO,” IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2010. pp. 686-689. Mar. 2010.
which has the following features:
1. Depth maps are interpreted according to the MPEG Informative
Recommendations in MPEG Doc. N8038.
2. Left image is rendered Right most pixel to the Left most pixel and Right Image is rendered vice versa. This is done to make sure that no background pixels would appear as foreground.
3. Disocclusions are filled with Background pixel extrapolation,
however with some small modifications. Disocclusions are filled in the opposite direction to rendering.
- This program implements the rendering framework that is used in the paper
D. De Silva, W. Fernando, and H. Kodikaraarachchi,
“A NEW MODE SELECTION TECHNIQUE FOR CODING DEPTH MAPS OF 3D VIDEO,” IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2010. pp. 686-689. Mar. 2010.
which has the following features:
1. Depth maps are interpreted according to the MPEG Informative
Recommendations in MPEG Doc. N8038.
2. Left image is rendered Right most pixel to the Left most pixel and Right Image is rendered vice versa. This is done to make sure that no background pixels would appear as foreground.
3. Disocclusions are filled with Background pixel extrapolation,
however with some small modifications. Disocclusions are filled in the opposite direction to rendering.
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Size: 1412096 |
Author: phonox |
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Description: 一个完整的EEMD自适应噪声 IEEE Int. Conf. on Acoust., Speech and Signal Proc. ICASSP-11, pp. 4144-4147, Prague (CZ)文章对应的matlab原始程序，验证可用 Example of the CEEMDAN performance, used in the work where CEEMDAN was first presented(Example of the CEEMDAN performance, used in the work where CEEMDAN was first presented,The corresponding matlab original program, Example of the CEEMDAN performance authentication, used in the work where CEEMDAN was first presented.)
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Size: 11264 |
Author: 千寻69
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Description: Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent
unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard
CS formulation, a codebook of transfer functions is proposed in a
matching pursuit (MP) framework for CS recovery. It is found that
MP is efficient and effective to recover CS encoded speech as well
as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge
to the same linear transform as direct VQ of the LP vector derived
from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain
approximation for a large variety of speech spectra.
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Size: 354304 |
Author: pashaa
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