Detailed explanation of C++ function recursion: Recursion in dynamic programming

Abstract: Recursive calls are implemented in C by calling its own function. The recursive solution of the Fibonacci sequence requires three components: basic conditions (n ​​is less than or equal to 1), recursive calls (solving F(n-1) and F(n-2) by itself), increment/decrement (n every recursion Decrease 1) at a time. The advantage is that the code is concise, but the disadvantage is that the space complexity is high and stack overflow may occur. For large data sets, it is recommended to use dynamic programming to optimize space complexity.

#C Detailed explanation of function recursion: Recursion in dynamic programming

Recursion is the process of a function calling itself. In C, a recursive function needs to have the following components:

• Basic conditions: when the recursion ends
• Recursive call: the function calls itself
• Increment/decrement: The calculation or modification used each time the function is called recursively

Practical case: Fibonacci sequence

The Fibonacci sequence is a sequence of numbers. Each number is the sum of the previous two numbers. It can be expressed as:

F(n) = F(n-1) F(n-2)

The following is a function that uses C to recursively solve the Fibonacci sequence:

int fibonacci(int n) {
  if (n <= 1) {
    return n;
  }
  return fibonacci(n-1) + fibonacci(n-2);
}

How to understand recursive solution of Fibonacci sequence

• ##Basic conditions: When n is less than or equal to 1, the recursion ends and n is returned .
• Recursive call: Otherwise, the function calls itself to solve for F(n-1) and F(n-2).
• Increment/decrement: n decreases by 1 for each recursion.

Advantages and Disadvantages

Advantages:

The code is concise and clear
• Easy to understand

Disadvantages:

High space complexity (save each recursive call in the stack)
• may occur Stack overflow (when the recursion depth is too large)

Tips:

For large data sets, it is recommended to use dynamic programming methods instead of recursion, to optimize space complexity.
• It is important to understand the recursion termination conditions to avoid infinite recursion.

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