Zeckendorf's Theorem (NonNeighbouring Fibonacci Representation) (original) (raw)

Zeckendorf's Theorem (Non-Neighbouring Fibonacci Representation)

Last Updated : 23 Jul, 2025

Zeckendorf's theorem states that every positive integer can be written uniquely as a sum of distinct non-neighbouring Fibonacci numbers. Two Fibonacci numbers are neighbours if they one come after other in Fibonacci Sequence (0, 1, 1, 2, 3, 5, ..). For example, 3 and 5 are neighbours, but 2 and 5 are not.

Given a number, find a representation of number as sum of non-consecutive Fibonacci numbers.

Examples:

Input: n = 10 Output: 8 2 8 and 2 are two non-consecutive Fibonacci Numbers and sum of them is 10.

Input: n = 30 Output: 21 8 1 21, 8 and 1 are non-consecutive Fibonacci Numbers and sum of them is 30.

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The idea is to use Greedy Algorithm.

1. Let n be input number

2. While n >= 0 a) Find the greatest Fibonacci Number smaller than n. Let this number be 'f'. Print 'f' b) n = n - f

C++ `

// C++ program for Zeckendorf's theorem. It finds // representation of n as sum of // non-neighbouring Fibonacci Numbers. #include <bits/stdc++.h> using namespace std;

// Returns the greatest Fibonacci Number smaller than // or equal to n. int nearestSmallerEqFib(int n) { // Corner cases if (n == 0 || n == 1) return n;

// Find the greatest Fibonacci Number smaller
// than n.
int f1 = 0, f2 = 1, f3 = 1;
while (f3 <= n) 
{
    f1 = f2;
    f2 = f3;
    f3 = f1 + f2;
}
return f2;

}

// Prints Fibonacci Representation of n using // greedy algorithm void printFibRepresntation(int n) { while (n > 0) { // Find the greates Fibonacci Number smaller // than or equal to n int f = nearestSmallerEqFib(n);

    // Print the found fibonacci number
    cout << f << " ";

    // Reduce n
    n = n - f;
}

}

// Driver code int main() { int n = 30; cout << "Non-neighbouring Fibonacci Representation of " << n << " is \n"; printFibRepresntation(n); return 0; }

Java

// Java program for Zeckendorf's theorem. It finds // representation of n as sum of non-neighbouring // Fibonacci Numbers. class GFG { public static int nearestSmallerEqFib(int n) { // Corner cases if (n == 0 || n == 1) return n;

    // Find the greatest Fibonacci Number smaller
    // than n.
    int f1 = 0, f2 = 1, f3 = 1;
    while (f3 <= n) {
        f1 = f2;
        f2 = f3;
        f3 = f1 + f2;
    }
    return f2;
}

// Prints Fibonacci Representation of n using
// greedy algorithm
public static void printFibRepresntation(int n)
{
    while (n > 0) {
        // Find the greates Fibonacci Number smaller
        // than or equal to n
        int f = nearestSmallerEqFib(n);

        // Print the found fibonacci number
        System.out.print(f + " ");

        // Reduce n
        n = n - f;
    }
}

// Driver method to test
public static void main(String[] args)
{
    int n = 30;
    System.out.println("Non-neighbouring Fibonacci "
                       + " Representation of " + n + " is");

    printFibRepresntation(n);
}

}

// Code Contributed by Mohit Gupta_OMG

Python3

Python program for Zeckendorf's theorem. It finds

representation of n as sum of non-neighbouring

Fibonacci Numbers.

Returns the greatest Fibonacci Number smaller than

or equal to n.

def nearestSmallerEqFib(n):

# Corner cases
if (n == 0 or n == 1):
    return n
   
# Finds the greatest Fibonacci Number smaller
# than n.
f1, f2, f3 = 0, 1, 1
while (f3 <= n):
    f1 = f2;
    f2 = f3;
    f3 = f1 + f2;
return f2;

Prints Fibonacci Representation of n using

greedy algorithm

def printFibRepresntation(n):

while (n>0):

    # Find the greates Fibonacci Number smaller
    # than or equal to n
    f = nearestSmallerEqFib(n);

    # Print the found fibonacci number
    print (f,end=" ")

    # Reduce n
    n = n-f

Driver code test above functions

n = 30 print ("Non-neighbouring Fibonacci Representation of", n, "is") printFibRepresntation(n)

C#

// C# program for Zeckendorf's theorem. // It finds the representation of n as // sum of non-neighbouring Fibonacci // Numbers. using System;

class GFG { public static int nearestSmallerEqFib(int n) { // Corner cases if (n == 0 || n == 1) return n;

    // Find the greatest Fibonacci
    // Number smaller than n.
    int f1 = 0, f2 = 1, f3 = 1;
    while (f3 <= n) {
        f1 = f2;
        f2 = f3;
        f3 = f1 + f2;
    }
    return f2;
}

// Prints Fibonacci Representation
// of n using greedy algorithm
public static void printFibRepresntation(int n)
{
    while (n > 0) {
        // Find the greates Fibonacci
        // Number smallerthan or equal
        // to n
        int f = nearestSmallerEqFib(n);

        // Print the found fibonacci number
        Console.Write(f + " ");

        // Reduce n
        n = n - f;
    }
}

// Driver method
public static void Main()
{
    int n = 40;
    Console.WriteLine("Non-neighbouring Fibonacci "
                      + " Representation of " + n + " is");

    printFibRepresntation(n);
}

}

// Code Contributed by vt_m

PHP

JavaScript

`

Output

Non-neighbouring Fibonacci Representation of 30 is 21 8 1

Time Complexity: O(N*LogN)
Auxiliary Space: O(1)

How does above Greedy Algorithm work?
Let the greatest Fibonacci number smaller than or equal to 'n' be fib(i) [i'th Fibonacci Number].
Then n - fib(i) will have its own representation as sum of non-neighbouring Fibonacci numbers.
All we want to make sure is that there is no neighbouring problem. By induction, n-fib(i) does not have neighbouring problem, then the only way n could have a neighbouring problem is if n-fib(i) uses fib(i-1) in its representation.
So all we have to further prove is that n-fib(i) does not use fib(i-1) in its representation
Let us prove it using contradiction. If n-fib(i) = fib(i-1) + fib(i-x) +..., then fib(i) cannot be the closest smallest Fibonacci number to n, since fib(i) + fib(i-1) itself is fib(i+1).
So if n-fib(i) contains fib(i-1) in its representation then fib(i+1) would be closer smaller fib number to n, contradicting our assumption that fib(i) is the closest smaller fib number to n.

Can this representation be useful?
Like Binary Representation. This can be an alternate representation to represent positive numbers. One important observation about this representation is, number of 1's in the Fibonacci representation tends to be much less than the number of 1's in the binary representation. Hence if in any application where it is more costly to store a 1 than to store a 0, it would make sense to use the fibonacci representation.