The random Fibonacci sequence is an integer random sequence , where f1 = f2 = 1 and the subsequent terms are determined from the random recurrence relation A run of the random Fibonacci sequence starts with 1,1 and the value of the each subsequent term is determined by a fair coin toss: given two consecutive elements of the sequence, the next element is either their sum or their difference with probability 1/2, independently of all the choices made previously. If in the random Fibonacci sequence the plus sign is chosen at each step, the corresponding run is the Fibonacci sequence, If the signs alternate in minus-plus-plus-minus-plus-plus-... pattern, the result is the sequence However, such patterns occur with vanishing probability in a random experiment. In a typical run, the terms will not follow a predictable pattern: Similarly to the deterministic case, the random Fibonacci sequence may be profitably described via matrices: where the signs are chosen independently for different n with equal probabilities for + or −. Thus where is a sequence of independent identically distributed random matricestaking values A or B with probability 1/2:
Growth rate
discovered that as n increases, the ratio of the successive terms of the Fibonacci sequence approaches the golden ratio which is approximately 1.61803. In 1765, Leonhard Euler published an explicit formula, known today as the Binet formula, It demonstrates that the Fibonacci numbers grow at an exponential rate equal to the golden ratioφ. In 1960, Hillel Furstenberg and Harry Kesten showed that for a general class of random matrix products, the norm grows as λn, where n is the number of factors. Their results apply to a broad class of random sequence generating processes that includes the random Fibonacci sequence. As a consequence, the nth root of |fn| converges to a constant valuealmost surely, or with probability one: An explicit expression for this constant was found by Divakar Viswanathin 1999. It uses Furstenberg's formula for the Lyapunov exponent of a random matrix product and integration over a certain fractal measure on the Stern–Brocot tree. Moreover, Viswanath computed the numerical value above using floating point arithmetics validated by an analysis of the rounding error.