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9.13 Implement the Fibonacci function iteratively (without using an array).

If a periodic sequence I ( n ) is shifted, the DFS coefficients are multiplied by a complex exponential. In other words, if z ( k ) are the DFS coefficients for P(n), the DFS coefficients for y(n) = 2(n - no) are

CHAP. 9]

f (k) = w f 0 2 ( k )

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914 Implement the recursive Ackermann function: A(0, n) = n + 1 A(m, 0) = A(m 1, 1), if m > 0 A(m, n) = A(m 1, A(m, n 1)), if m > 0 and n > 0 915 Prove Pascal s recurrence relation (page 170) 916 Trace the recursive implementation of the Euclidean Algorithm (Example 913 on page 171) on the call gcd(385, 231) 917 Implement the Euclidean Algorithm (page 171) iteratively 918 Implement the recursive Euclidean Algorithm using the integer remainder operator % instead of repeated subtraction 919 Implement the Euclidean Algorithm iteratively using the integer remainder operator % instead of repeated subtraction 920 Use mathematical induction to prove that the recursive implementation of the Fibonacci function (Example 96 on page 167) is correct 921 Use mathematical induction to prove that the recursive function in Problem 9.

Similarly, if P (n ) is multiplied by a complex exponential,

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9.35 Use these formulas to implement the hyperbolic sine and hyperbolic cosine functions recursively: sinh2x = 2sinhxcoshx cosh2x = 1 + 2(sinhx)2 sin x x + x 3/6 cos x 1 + x 2/2 Compare your results with the corresponding values of the Math.sinh() and Math.cosh() methods. 9.36 Use these trigonometric formulas to implement the tangent function recursively: tan2 = 2tan /(1 tan2 ) tan x x + x 3/3 Compare your results with the corresponding values of the Math.tan() method. 9.37 Implement a recursive function that evaluates a polynomial a0 + a1 x + a2 x2 + + a3 x3, where the n+1 coefficients ai are passed to the function in an array along with the degree n.

the DFS coefficients of i ( n ) are shifted:

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4 is correct 922 Use mathematical induction to prove that the recursive function in Problem 95 is correct 923 Use mathematical induction to prove that the recursive function in Problem 98 is correct 924 Use mathematical induction to prove that the recursive function in Problem 912 is correct 925 The computable domain of a function is the set of inputs for which the function can produce correct results Determine empirically the computable domain of the factorial function implemented in Example 92 on page 165 926 Determine empirically the computable domain of the sum(b,n) function implemented in Problem 92 on page 177, using b = 2 927 Determine empirically the computable domain of the Fibonacci function implemented in Example 93 on page 166 928 Determine empirically the computable domain of the recursive binomial coefficient function (Example 9.

Y (k) = $(k + k,,)

9.1 The basis of a recursive function is its starting point in its definition and its final step when it is being called recursively; it is what stops the recursion. The recursive part of a recursive function is the assignment that includes the function on the right side of the assignment operator, causing the function to call itself; it is what produces the repetition. For example, in the factorial function, the basis is n! = 1 if n = 0, and the recursive part is n! = n (n 1) if n > 0. The call factorial(10) will generate 10 recursive calls. The call f(6) to the Fibonacci function will generate 14 + 8 = 22 recursive calls because it calls f(5) and f(4), which generate 14 and 8 recursive calls, respectively. A recursive solution is often easier to understand than its equivalent iterative solution. But recursion usually runs more slowly than iteration. Direct recursion is where a function calls itself. Indirect recursion is where a group of functions call each other.

1f h(n) and i ( n ) are periodic with a period N with DFS coefficients &(k) and g ( k ) , respectively, the sequence with DFS coefficients F(k)= 4 (k)f (k)

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