Time series segmentation using a novel adaptive eigendecomposition algorithm

Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology

Volumn 32, Issue 1-2, 2002, Pages 7-17

  Rao, Yadunandana N ^a   Principe, Jose C ^a  

^a University of Florida   (United States)

Author keywords

Eigendecomposition; GLRT; PCA; Segmentation

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; ADAPTIVE ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; EIGENVALUES AND EIGENFUNCTIONS; EXPERT SYSTEMS; GRADIENT METHODS; MAXIMUM LIKELIHOOD ESTIMATION; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; TIME SERIES ANALYSIS;

EIGENDECOMPOSITION; GATED EXPERTS; GENERALIZED LIKELIHOOD RATIO TEST; GRADIENT SEARCH METHODS; MIXTURE MODELS; SPEECH SEGMENTATION; TIME SERIES SEGMENTATION;

SIGNAL FILTERING AND PREDICTION;

EID: 0036688592     PISSN: 13875485     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1016355116053     Document Type: Article

References (30)

1. Nonlinear gated experts for time series: Discovering regimes and avoiding overfitting
2. Competitive principal component analysis for locally stationary time series
3. A new statistical approach for the automatic segmentation of continuous speech signals
4. On the use of neural networks in the generalized likelihood ratio test for detecting abrupt changes in signals
5. A fast on-line generalized eigendecomposition algorithm for time series segmentation
6. Algorithms for eigendecomposition and time series segmentation
7. Artificial neural networks for feature extraction and multivariate data projection
8. Adaptive principal component extraction (APEX) and applications
9. A simplified neuron model as a principal component analyzer
10. Optimal unsupervised learning in a single-layer linear feedforward neural network
11. A self-organizing network for principal component analysis
12. Least mean square error reconstruction principle for self-organizing neural nets
13. Self-organizing algorithms for generalized eigendecomposition
14. Algorithms for accelerated convergence of adaptive PCA
15. Fast subspace tracking and neural network learning by a novel information criterion
16. Natural power method for fast subspace tracking
17. A fast on-line algorithm for PCA and its convergence characteristics
18. Analysis of recursive stochastic algorithms
19. The CNEL rule: A novel on-line algorithm for principal component analysis
20. Gated competitive systems for unsupervised segmentation and modeling of piecewise stationary signals