Neural networks for blind decorrelation of signals

S.C. Douglas , A Cichocki


We analyze and extend a class of adaptive networks for second-order blind decorrelation of instantaneous signal mixtures. First, we compare the performance of the single-layer neural network employing global knowledge of the adaptive coefficients with a similar structure whose coefficients are adapted via local output connections. Through statistical analyzes, the convergence behaviors and stability bounds for the algorithms' step sizes are studied and derived. Second, we analyze the behaviors of locally adaptive multilayer decorrelation networks and quantify their performances for poorly conditioned signal mixtures. Third, we derive a robust locally adaptive network structure based on a posteriori output signals that remains stable for any step-size value. Finally, we present an extension of the locally adaptive network for linear-phase temporal and spatial whitening of multichannel signals. Simulations verify the analyses and indicate the usefulness of the locally adaptive networks for decorrelating signals in space and time
Author S.C. Douglas
S.C. Douglas,,
, A Cichocki (FEIT / RE)
A Cichocki,,
- The Institute of Radioelectronics
Journal seriesIEEE Transactions on Signal Processing, ISSN 1053-587X
Issue year1997
Keywords in Englishadaptive coefficients, adaptive networks, adaptive signal processing, adaptive systems, Algorithm design and analysis, algorithm step sizes, a posteriori output signals, conditioned signal mixtures, convergence, convergence of numerical methods, correlation methods, Decorrelation, global knowledge, instantaneous signal mixtures, linear phase temporal whitening, locally adaptive multilayer decorrelation networks, local output connections, multichannel signals, Multi-layer neural network, multilayer perceptrons, neural networks, performance, performance analysis, robustness, second order blind decorrelation, Signal analysis, simulations, single layer neural network, spatial whitening, Stability analysis, stability bounds, statistical analysis
Score (nominal)40
Publication indicators WoS Impact Factor: 2006 = 1.57 (2) - 2007=2.525 (5)
Citation count*105 (2014-02-08)
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