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We consider certain Fibonacci-like sequences perturbed with a random noise. Our main result is that converges in distribution, as goes to infinity, to a random variable with Pareto-like distribution tails. We show that $s=\lim_{x\to \infty} \frac{-\log P(W>x)}{\log x}$ is a monotonically decreasing characteristic of the input noise, and hence can serve as a measure of its strength in the model. Heuristically, the heavy-taliped limiting distribution, versus a light-tailed one with can be interpreted as an evidence supporting the idea that the noise is “singular” in the sense that it is “big” even in a “slightly” perturbed sequence.

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