Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Neural networks for pattern recognition
Neural networks for pattern recognition
Discrete Random Signals and Statistical Signal Processing
Discrete Random Signals and Statistical Signal Processing
Detection of Signals in Noise
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Blind Source Separation Using Temporal Predictability
Neural Computation
Fractals in Science
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The paper presents a new method for randomness assessment in data with temporal structure. In this approach we perform multistage covariance analysis on several parts of the signal to synthesize information about variability and internal dependencies included in its structure. This allows us to identify deterministic cycles or to detect the level of randomness in signals what is an important issue for the design of transactional, prediction and filtration systems. To confirm validity of the proposed method we tested it on simulated and real financial time series.