Estimation of time delays between unknown colored signals
Signal Processing
Signal Processing - From signal processing theory to implementation
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Recognizing faces with PCA and ICA
Computer Vision and Image Understanding - Special issue on Face recognition
Analysis of sparse representation and blind source separation
Neural Computation
Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
ACM SIGGRAPH 2004 Papers
ICA for watermarking digital images
The Journal of Machine Learning Research
Higher Order Whitening of Natural Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Extrapolation, Interpolation, and Smoothing of Stationary Time Series
Extrapolation, Interpolation, and Smoothing of Stationary Time Series
Image Classification and Retrieval using Correlation
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blind separation of delayed sources based on information maximization
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06
Time delay estimation in room acoustic environments: an overview
EURASIP Journal on Applied Signal Processing
Non-negative matrix factorization with α-divergence
Pattern Recognition Letters
Underdetermined audio source separation from anechoic mixtures with long time delay
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Shifted independent component analysis
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Supervised and semi-supervised separation of sounds from single-channel mixtures
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Learning of translation-invariant independent components: multivariate anechoic mixtures
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Learning shapes for image classification and retrieval
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Image deblurring in the presence of salt-and-pepper noise
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Optimal kernels for nonstationary spectral estimation
IEEE Transactions on Signal Processing
Multitaper Time-Frequency Reassignment for Nonstationary Spectrum Estimation and Chirp Enhancement
IEEE Transactions on Signal Processing
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
Time delay and spatial signature estimation using knownasynchronous signals
IEEE Transactions on Signal Processing
Blind source separation based on time-frequency signalrepresentations
IEEE Transactions on Signal Processing
Blind Separation of Superimposed Shifted Images Using Parameterized Joint Diagonalization
IEEE Transactions on Image Processing
A "nonnegative PCA" algorithm for independent component analysis
IEEE Transactions on Neural Networks
Sparse component analysis and blind source separation of underdetermined mixtures
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
Blind source separation problems emerge in many applications, where signals can be modeled as superpositions of multiple sources. Many popular applications of blind source separation are based on linear instantaneous mixture models. If specific invariance properties are known about the sources, for example, translation or rotation invariance, the simple linear model can be extended by inclusion of the corresponding transformations. When the sources are invariant against translations (spatial displacements or time shifts) the resulting model is called an anechoic mixing model. We present a new algorithmic framework for the solution of anechoic problems in arbitrary dimensions. This framework is derived from stochastic time-frequency analysis in general, and the marginal properties of the Wigner-Ville spectrum in particular. The method reduces the general anechoic problem to a set of anechoic problems with non-negativity constraints and a phase retrieval problem. The first type of subproblem can be solved by existing algorithms, for example by an appropriate modification of non-negative matrix factorization (NMF). The second subproblem is solved by established phase retrieval methods. We discuss and compare implementations of this new algorithmic framework for several example problems with synthetic and real-world data, including music streams, natural 2D images, human motion trajectories and two-dimensional shapes.