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Register a new userGrowth rate for the expected value of a generalized random Fibonacci sequence
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Authors
Elise Janvresse
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A random Fibonacci sequence is defined by the relation g_n = | g_{n-1} +/- g_{n-2} |, where the +/- sign is chosen by tossing a balanced coin for each n. We generalize these sequences to the case when the coin is unbalanced (denoting by p the probability of a +), and the recurrence relation is of the form g_n = |lambda g_{n-1} +/- g_{n-2} |. When lambda >=2 and 0 < p <= 1, we prove that the expected value of g_n grows exponentially fast. When lambda = lambda_k = 2 cos(pi/k) for some fixed integer k>2, we show that the expected value of g_n grows exponentially fast for p>(2-lambda_k)/4 and give an algebraic expression for the growth rate. The involved methods extend (and correct) those introduced in a previous paper by the second author.
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We study the generalized random Fibonacci sequences defined by their first nonnegative terms and for $nge 1$, $F_{n+2} = lambda F_{n+1} pm F_{n}$ (linear case) and $widetilde F_{n+2} = |lambda widetilde F_{n+1} pm widetilde F_{n}|$ (non-linear case), where each $pm$ sign is independent and either $+$ with probability $p$ or $-$ with probability $1-p$ ($0<ple 1$). Our main result is that, when $lambda$ is of the form $lambda_k = 2cos (pi/k)$ for some integer $kge 3$, the exponential growth of $F_n$ for $0<ple 1$, and of $widetilde F_{n}$ for $1/k < ple 1$, is almost surely positive and given by $$ int_0^infty log x d u_{k, rho} (x), $$ where $rho$ is an explicit function of $p$ depending on the case we consider, taking values in $[0, 1]$, and $ u_{k, rho}$ is an explicit probability distribution on $RR_+$ defined inductively on generalized Stern-Brocot intervals. We also provide an integral formula for $0<ple 1$ in the easier case $lambdage 2$. Finally, we study the variations of the exponent as a function of $p$.
We study two kinds of random Fibonacci sequences defined by $F_1=F_2=1$ and for $nge 1$, $F_{n+2} = F_{n+1} pm F_{n}$ (linear case) or $F_{n+2} = |F_{n+1} pm F_{n}|$ (non-linear case), where each sign is independent and either + with probability $p$ or - with probability $1-p$ ($0<ple 1$). Our main result is that the exponential growth of $F_n$ for $0<ple 1$ (linear case) or for $1/3le ple 1$ (non-linear case) is almost surely given by $$int_0^infty log x d u_alpha (x), $$ where $alpha$ is an explicit function of $p$ depending on the case we consider, and $ u_alpha$ is an explicit probability distribution on $RR_+$ defined inductively on Stern-Brocot intervals. In the non-linear case, the largest Lyapunov exponent is not an analytic function of $p$, since we prove that it is equal to zero for $0<ple1/3$. We also give some results about the variations of the largest Lyapunov exponent, and provide a formula for its derivative.
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