|
| 1 | +--- |
| 2 | +id: Fibonacci-Numbers |
| 3 | +title: Fibonacci-Numbers |
| 4 | +sidebar_label: Fibonacci-Numbers |
| 5 | +tags: |
| 6 | + - Fibonacci |
| 7 | + - Dynamic Programming |
| 8 | + - Recursion |
| 9 | + - Algorithms |
| 10 | +--- |
| 11 | + |
| 12 | +## Problem Description |
| 13 | + |
| 14 | +| Problem Statement | Solution Link | LeetCode Profile | |
| 15 | +| :------------------------------------------------------ | :------------------------------------------------------------------------- | :------------------------------------------------------ | |
| 16 | +| [Fibonacci-Numbers](https://leetcode.com/problems/Fibonacci-Numbers/description/) | [Fibonacci-Numbers Solution on LeetCode](https://leetcode.com/problems/Fibonacci-Numbers/solutions/) | [Nikita Saini](https://leetcode.com/u/Saini_Nikita/) | |
| 17 | + |
| 18 | +## Problem Description |
| 19 | + |
| 20 | +The Fibonacci numbers, commonly denoted F(n), form a sequence, called the Fibonacci sequence, such that each number is the sum of the two preceding ones, starting from 0 and 1. That is, |
| 21 | + |
| 22 | +- F(0) = 0 |
| 23 | +- F(1) = 1 |
| 24 | +- F(n) = F(n-1) + F(n-2) for n > 1 |
| 25 | + |
| 26 | +Given an integer n, calculate F(n). |
| 27 | + |
| 28 | +### Examples |
| 29 | + |
| 30 | +### Example 1 |
| 31 | +**Input:** `n = 2` |
| 32 | +**Output:** `1` |
| 33 | +**Explanation:** `F(2) = F(1) + F(0) = 1 + 0 = 1.` |
| 34 | + |
| 35 | +### Example 2 |
| 36 | +**Input:** `n = 3` |
| 37 | +**Output:** `2` |
| 38 | +**Explanation:** `F(3) = F(2) + F(1) = 1 + 1 = 2.` |
| 39 | + |
| 40 | +### Example 3 |
| 41 | +**Input:** `n = 4` |
| 42 | +**Output:** `3` |
| 43 | +**Explanation:** `F(4) = F(3) + F(2) = 2 + 1 = 3.` |
| 44 | + |
| 45 | +## Constraints |
| 46 | + |
| 47 | +- `0 <= n <= 30` |
| 48 | + |
| 49 | +## Approach |
| 50 | + |
| 51 | +There are several approaches to solve the Fibonacci problem: |
| 52 | +1. **Recursive Approach**: Simple but inefficient due to redundant calculations. |
| 53 | +2. **Iterative Approach**: Efficient using a loop to build up the Fibonacci sequence. |
| 54 | +3. **Dynamic Programming Approach**: Efficiently store computed results to avoid redundant calculations. |
| 55 | + |
| 56 | +## Solution in different languages |
| 57 | + |
| 58 | +### Solution in Python |
| 59 | +```python |
| 60 | +def fibonacci(n): |
| 61 | + if n == 0: |
| 62 | + return 0 |
| 63 | + elif n == 1: |
| 64 | + return 1 |
| 65 | + |
| 66 | + prev1, prev2 = 0, 1 |
| 67 | + for i in range(2, n + 1): |
| 68 | + current = prev1 + prev2 |
| 69 | + prev1, prev2 = prev2, current |
| 70 | + |
| 71 | + return prev2 |
| 72 | + |
| 73 | +# Example usage: |
| 74 | +n = 4 |
| 75 | +print(fibonacci(n)) # Output: 3 |
| 76 | +``` |
| 77 | + |
| 78 | +### Solution in Java |
| 79 | + |
| 80 | +```java |
| 81 | +public class Solution { |
| 82 | + public int fibonacci(int n) { |
| 83 | + if (n == 0) { |
| 84 | + return 0; |
| 85 | + } else if (n == 1) { |
| 86 | + return 1; |
| 87 | + } |
| 88 | + |
| 89 | + int prev1 = 0, prev2 = 1; |
| 90 | + for (int i = 2; i <= n; i++) { |
| 91 | + int current = prev1 + prev2; |
| 92 | + prev1 = prev2; |
| 93 | + prev2 = current; |
| 94 | + } |
| 95 | + |
| 96 | + return prev2; |
| 97 | + } |
| 98 | + |
| 99 | + public static void main(String[] args) { |
| 100 | + Solution solution = new Solution(); |
| 101 | + int n = 4; |
| 102 | + System.out.println(solution.fibonacci(n)); // Output: 3 |
| 103 | + } |
| 104 | +} |
| 105 | +``` |
| 106 | + |
| 107 | +### Solution in C++ |
| 108 | + |
| 109 | +```cpp |
| 110 | +#include <iostream> |
| 111 | +using namespace std; |
| 112 | + |
| 113 | +int fibonacci(int n) { |
| 114 | + if (n == 0) { |
| 115 | + return 0; |
| 116 | + } else if (n == 1) { |
| 117 | + return 1; |
| 118 | + } |
| 119 | + |
| 120 | + int prev1 = 0, prev2 = 1; |
| 121 | + for (int i = 2; i <= n; i++) { |
| 122 | + int current = prev1 + prev2; |
| 123 | + prev1 = prev2; |
| 124 | + prev2 = current; |
| 125 | + } |
| 126 | + |
| 127 | + return prev2; |
| 128 | +} |
| 129 | + |
| 130 | +int main() { |
| 131 | + int n = 4; |
| 132 | + cout << fibonacci(n) << endl; // Output: 3 |
| 133 | + return 0; |
| 134 | +} |
| 135 | +``` |
| 136 | +
|
| 137 | +### Solution in C |
| 138 | +
|
| 139 | +```c |
| 140 | +#include <stdio.h> |
| 141 | +
|
| 142 | +int fibonacci(int n) { |
| 143 | + if (n == 0) { |
| 144 | + return 0; |
| 145 | + } else if (n == 1) { |
| 146 | + return 1; |
| 147 | + } |
| 148 | + |
| 149 | + int prev1 = 0, prev2 = 1; |
| 150 | + for (int i = 2; i <= n; i++) { |
| 151 | + int current = prev1 + prev2; |
| 152 | + prev1 = prev2; |
| 153 | + prev2 = current; |
| 154 | + } |
| 155 | + |
| 156 | + return prev2; |
| 157 | +} |
| 158 | +
|
| 159 | +int main() { |
| 160 | + int n = 4; |
| 161 | + printf("%d\n", fibonacci(n)); // Output: 3 |
| 162 | + return 0; |
| 163 | +} |
| 164 | +``` |
| 165 | + |
| 166 | +### Solution in JavaScript |
| 167 | + |
| 168 | +```javascript |
| 169 | +function fibonacci(n) { |
| 170 | + if (n === 0) { |
| 171 | + return 0; |
| 172 | + } else if (n === 1) { |
| 173 | + return 1; |
| 174 | + } |
| 175 | + |
| 176 | + let prev1 = 0, prev2 = 1; |
| 177 | + for (let i = 2; i <= n; i++) { |
| 178 | + let current = prev1 + prev2; |
| 179 | + prev1 = prev2; |
| 180 | + prev2 = current; |
| 181 | + } |
| 182 | + |
| 183 | + return prev2; |
| 184 | +} |
| 185 | + |
| 186 | +// Example usage: |
| 187 | +let n = 4; |
| 188 | +console.log(fibonacci(n)); // Output: 3 |
| 189 | +``` |
| 190 | + |
| 191 | +## Step-by-Step Algorithm |
| 192 | + |
| 193 | +1. **Base Cases**: |
| 194 | + - If \( n = 0 \), return 0. |
| 195 | + - If \( n = 1 \), return 1. |
| 196 | + |
| 197 | +2. **Iterative Calculation**: |
| 198 | + - Initialize `prev1` to 0 and `prev2` to 1. |
| 199 | + - Iterate from 2 to n: |
| 200 | + - Calculate `current` as `prev1 + prev2`. |
| 201 | + - Update `prev1` to `prev2` and `prev2` to `current`. |
| 202 | + - After the loop, `prev2` contains the Fibonacci number for \( n \). |
| 203 | + |
| 204 | +## Conclusion |
| 205 | + |
| 206 | +The Fibonacci sequence can be efficiently computed using iterative or dynamic programming approaches to avoid redundant calculations. These methods provide a clear improvement over the naive recursive approach, especially for larger values of \( n \). The iterative approach is straightforward and runs in \( O(n) \) time complexity with \( O(1) \) space complexity, making it suitable for the given constraints \( 0 \leq n \leq 30 \). |
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