Filters








13,784 Hits in 2.9 sec

An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters

Weifeng Liu, Il Park, J.C. Principe
2009 IEEE Transactions on Neural Networks  
This paper discusses an information theoretic approach of designing sparse kernel adaptive filters.  ...  Based on this concept, we propose a systematic sparsification scheme, which can drastically reduce the time and space complexity without harming the performance of kernel adaptive filters.  ...  We are particularly interested in applying the surprise concept to designing sparse kernel adaptive filters.  ... 
doi:10.1109/tnn.2009.2033676 pmid:19923047 fatcat:5xox25gkwfhejdpkpnstajxm6e

Efficient auditory coding

Evan C. Smith, Michael S. Lewicki
2006 Nature  
These results indicate that the auditory code might approach an information theoretic optimum and that the acoustic structure of speech might be adapted to the coding capacity of the mammalian auditory  ...  To allow the kernel functions to assume arbitrary potential shapes, we represented each kernel f m by a vector of length L m , where each element is an independent parameter of the model.  ...  Empirical data in this paper were acquired from Boston University's Earlab, an online, freely accessible auditory database (http://earlab.bu.edu).  ... 
doi:10.1038/nature04485 pmid:16495999 fatcat:35caqt3okfhindhxxgnxdxvfpy

New Trends in Biologically-Inspired Audio Coding [chapter]

Ramin Pichevar, Hossein Najaf-Zadeh, Louis Thibault, Hassan Lahdili
2010 Signal Processing  
We show that the introduction of adaptiveness in the selection of gammachirp kernels enhances the compression rate compared to the case where the kernels are non-adaptive.  ...  The approach is applied to different audio signals and results are discussed and compared. This work is a first step towards the design of a high-quality auditory-inspired "object-based" audio coder.  ...  With the adaptive scheme, we observe an average drop of 45% in the bitrate compared to the nonadaptive approach.  ... 
doi:10.5772/8529 fatcat:utucwxa7cvgfjjrje3332upl2y

2019 Index IEEE Transactions on Signal and Information Processing over Networks Vol. 5

2019 IEEE Transactions on Signal and Information Processing over Networks  
., +, TSIPN Dec. 2019 669-683 Distributed Estimation Over an Adaptive Diffusion Network Based on the Family of Affine Projection Algorithms.  ...  ., +, TSIPN Dec. 2019 669-683 Distributed Estimation Over an Adaptive Diffusion Network Based on the Family of Affine Projection Algorithms.  ... 
doi:10.1109/tsipn.2019.2959414 fatcat:ixpx5rg5l5hshkt2ppvie3afqe

Sparse data interpolation using the geodesic distance affinity space [article]

Mikhail G. Mozerov, and Fei Yang, Joost van de Weijer
2019 arXiv   pre-print
In this paper, we adapt the geodesic distance-based recursive filter to the sparse data interpolation problem. The proposed technique is general and can be easily applied to any kind of sparse data.  ...  EXPERIMENTS The experiments have been designed to demonstrate the potential of the proposed approach.  ...  Fortunately, if the sparse data has additional information correlated with the restored function we can solve the sparse data interpolation more accurately with the class of edge preserving filters.  ... 
arXiv:1905.02229v1 fatcat:23cocc2hl5efxlbtli7v64c43a

Entropy-Constrained Spike Modulus Quantization In A Bio-Inspired Universal Audio Coder

Hassan Lahdili, Hossein Najaf-Zadeh, Ramin Pichevar, Louis Thibault
2008 Zenodo  
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008  ...  Our proposed method in [4] was an adaptive version of [16] and uses gammachirp kernels instead of the original gammatones used in [16] .  ...  It is therefore impossible to derive a closed-form theoretical solution for the optimalα i in the case of sparse representations. Hence, we should use adaptive optimization techniques.  ... 
doi:10.5281/zenodo.40962 fatcat:lgudlpcgabhzvgjvmq2fxywjee

Uniform and Non-Uniform Single Image Deblurring Based on Sparse Representation and Adaptive Dictionary Learning

Ashwini M. Deshpande, Suprava Patnaik
2014 The International Journal of Multimedia & Its Applications  
The approach taken is based on sparse and redundant representations over adaptively training dictionaries from single blurred-noisy image itself.  ...  Comprehensive experimental evaluation demonstrate that the proposed framework integrating the sparseness property of images, adaptive dictionary training and iterative deblurring scheme together significantly  ...  ACKNOWLEDGEMENTS The authors would like to thank anonymous reviewers for their constructive comments and valuable suggestions that helped to improve the quality of this work.  ... 
doi:10.5121/ijma.2013.6104 fatcat:gnn7s3ovczhfnidi6cx7327x6q

Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments [article]

Wentao Ma, Hua Qua, Guan Gui, Li Xu, Jihong Zhaoa, Badong Chen
2015 arXiv   pre-print
Sparse adaptive channel estimation problem is one of the most important topics in broadband wireless communications systems due to its simplicity and robustness.  ...  To address this problem, we propose in this work a robust sparse adaptive filtering algorithm using correntropy induced metric (CIM) penalized maximum correntropy criterion (MCC) rather than conventional  ...  Acknowledgements This work was supported by National Natural Science Foundation of China (NSFC) grants (No.  ... 
arXiv:1503.00802v2 fatcat:ckgolwwek5hpjbehaij26wx2du

Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments

Wentao Ma, Hua Qu, Guan Gui, Li Xu, Jihong Zhao, Badong Chen
2015 Journal of the Franklin Institute  
Sparse adaptive channel estimation problem is one of the most important topics in broadband wireless communications systems due to its simplicity and robustness.  ...  To address this problem, we propose in this work a robust sparse adaptive filtering algorithm using correntropy induced metric (CIM) penalized maximum correntropy criterion (MCC) rather than conventional  ...  Acknowledgements This work was supported by National Natural Science Foundation of China (NSFC) grants (No.  ... 
doi:10.1016/j.jfranklin.2015.03.039 fatcat:7d7iowflqngq5iif4dpl2fjsi4

Efficient Fusion of Sparse and Complementary Convolutions [article]

Chun-Fu Chen, Quanfu Fan, Marco Pistoia, Gwo Giun Lee
2018 arXiv   pre-print
The core of our approach is an efficient network module that linearly combines sparse kernels to yield feature representations as strong as those from regular kernels.  ...  Different from previous works that learn sparsity in models, we directly employ hand-crafted kernels with regular sparse patterns, which result in the computational gain in practice without sophisticated  ...  These approaches focus on filter-level pruning, which removes an entire filter if it's insignificant.  ... 
arXiv:1808.02167v3 fatcat:dygeb3beqnb4zagsimlcctpkum

2019 Index IEEE Transactions on Signal Processing Vol. 67

2019 IEEE Transactions on Signal Processing  
Zhao, J., +, Unified Approach to the Statistical Convergence Analysis of Frequency-Domain Adaptive Filters.  ...  ., +, TSP June 1, 2019 2923-2936 Theoretical Analysis of the Peak-to-Average Power Ratio and Optimal Pulse Shaping Filter Design for GFDM Systems.  ...  M Machine bearings Quickest Change Detection in the Presence of a Nuisance Change. Lau, T.S., +, TSP Oct. 15  ... 
doi:10.1109/tsp.2020.2968163 fatcat:dvvpqntb2rc2bjed5nnk4xora4

2020 Index IEEE Signal Processing Letters Vol. 27

2020 IEEE Signal Processing Letters  
., +, LSP 2020 6-10 Fraud An Information-Theoretic Approach to Personalized Explainable Machine Learning.  ...  ., +, LSP 2020 1735-1739 Decision making An Information-Theoretic Approach to Personalized Explainable Machine Learning.  ... 
doi:10.1109/lsp.2021.3055468 fatcat:wfdtkv6fmngihjdqultujzv4by

Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior

Haichao Zhang, David Wipf, Yanning Zhang
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
This coupled penalty function enjoys a number of desirable properties, including a mechanism whereby the relative-concavity or shape is adapted as a function of the intrinsic quality of each blurry observation  ...  The underlying multi-image blind deconvolution problem is solved by linking all of the observations together via a Bayesian-inspired penalty function which couples the unknown latent image, blur kernels  ...  Acknowledgements This work was done while the first author was an intern at Microsoft Research Asia.  ... 
doi:10.1109/cvpr.2013.140 dblp:conf/cvpr/ZhangWZ13 fatcat:qyqsj4ig4nht3bsampn6f3kgsa

Nonedge-Specific Adaptive Scheme for Highly Robust Blind Motion Deblurring of Natural Imagess

Chao Wang, Yong Yue, Feng Dong, Yubo Tao, Xiangyin Ma, Gordon Clapworthy, Hai Lin, Xujiong Ye
2013 IEEE Transactions on Image Processing  
Blind motion deblurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel.  ...  We classify the existing methods into two schemes and analyze their robustness using an image set consisting of 1.2 million natural images.  ...  While NEAS belongs to the non-edge specific scheme, it is designed to deal with statistical variations of images and increases the robustness by adopting an adaptive approach.  ... 
doi:10.1109/tip.2012.2219548 pmid:23008258 fatcat:pi3sl5cvi5elri3kubufwp5qua

Localized Spectral Graph Filter Frames: A Unifying Framework, Survey of Design Considerations, and Numerical Comparison (Extended Cut) [article]

David I Shuman
2020 arXiv   pre-print
After showing how this class encompasses a variety of approaches from spectral graph wavelets to graph filter banks, we focus on the two main questions of how to design the spectral filters and how to  ...  signals has been an active area of research over the last decade.  ...  ACKNOWLEDGMENTS The author would like to thank the anonymous reviewers and Hamid Behjat for constructive feedback on earlier versions of this article.  ... 
arXiv:2006.11220v2 fatcat:2fhnkgrlgfau7o4m2aoisoflju
« Previous Showing results 1 — 15 out of 13,784 results