A decomposition for three-way arrays
SIAM Journal on Matrix Analysis and Applications
A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications
Subspace methods for multimicrophone speech dereverberation
EURASIP Journal on Applied Signal Processing
Multiway analysis of epilepsy tensors
Bioinformatics
Multitarget identification and localization using bistatic MIMO radar systems
EURASIP Journal on Advances in Signal Processing
Enhanced Line Search: A Novel Method to Accelerate PARAFAC
SIAM Journal on Matrix Analysis and Applications
A PARAFAC-based technique for detection and localization of multiple targets in a MIMO radar system
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A comparison of algorithms for fitting the PARAFAC model
Computational Statistics & Data Analysis
Bi-iterative least-square method for subspace tracking
IEEE Transactions on Signal Processing - Part II
Bi-iteration SVD subspace tracking algorithms
IEEE Transactions on Signal Processing
Subspace methods for the blind identification of multichannel FIRfilters
IEEE Transactions on Signal Processing
Blind PARAFAC receivers for DS-CDMA systems
IEEE Transactions on Signal Processing
Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization
IEEE Transactions on Signal Processing
Parallel factor analysis in sensor array processing
IEEE Transactions on Signal Processing
Sliding window adaptive SVD algorithms
IEEE Transactions on Signal Processing
Blind identification and source separation in 2×3 under-determined mixtures
IEEE Transactions on Signal Processing
Higher Order SVD Analysis for Dynamic Texture Synthesis
IEEE Transactions on Image Processing
Batch and adaptive PARAFAC-based blind separation of convolutive speech mixtures
IEEE Transactions on Audio, Speech, and Language Processing
Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar
IEEE Transactions on Signal Processing
Tensor space-time (TST) coding for MIMO wireless communication systems
Signal Processing
ParCube: sparse parallelizable tensor decompositions
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Closed-Form Blind 2D-DOD and 2D-DOA Estimation for MIMO Radar with Arbitrary Arrays
Wireless Personal Communications: An International Journal
Hi-index | 35.69 |
The PARAFAC decomposition of a higher-order tensor is a powerful multilinear algebra tool that becomes more and more popular in a number of disciplines. Existing PARAFAC algorithms are computationally demanding and operate in batch mode--both serious drawbacks for on-line applications. When the data are serially acquired, or the underlying model changes with time, adaptive PARAFAC algorithms that can track the sought decomposition at low complexity would be highly desirable. This is a challenging task that has not been addressed in the literature, and the topic of this paper. Given an estimate of the PARAFAC decomposition of a tensor at instant t, we propose two adaptive algorithms to update the decomposition at instant t + 1, the new tensor being obtained from the old one after appending a new slice in the 'time' dimension. The proposed algorithms can yield estimation performance that is very close to that obtained via repeated application of state-of-art batch algorithms, at orders of magnitude lower complexity. The effectiveness of the proposed algorithms is illustrated using a MIMO radar application (tracking of directions of arrival and directions of departure) as an example.