Chaos and Time-Series Analysis
Chaos and Time-Series Analysis
Nonlinear Time Series Analysis
Nonlinear Time Series Analysis
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The paper describes a new methodallowing the representation of an image through weights of the chaotic neural oscillators network. The proposed algorithm uses the permutation entropy of the individual oscillator to form values associated with the output image. Oscillators interaction produce generalized synchronization leading to the clustering and pattern formation. In the narrow range of the weights among oscillators the spontaneous clustering decrease the noise. Increased values lead to the pattern formation and image distortion.