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public class TestSquares { public static void main(String[] args) { Primes.setSize(1000); for (int n = 1; n < 100; n++) { for (int i = n*n+1; i < (n+1)*(n+1); i++) { if (Primes.isPrime(i)) { System.out.printf("%d < %d < %d%n", n*n, i, (n+1)*(n+1)); break; } } } } } public class TestMersenne { public static void main(String[] args) { Primes.setSize(1000); for (int p = Primes.next(); p < 30; p = Primes.next()) { int n = (int)Math.round(Math.pow(2,p)) - 1; System.out.printf("%d\t2^%d-1%d", p, p, n); if (Primes.isPrime(n)) { System.out.println(" is prime "); } else { System.out.println(" is not prime "); } } } } boolean isPalindromic(int n) { if (n < 0) { return false; } int p10=1; // make p10 is the greatest power of 10 that is < n while (p10 < n) { p10 *= 10; } p10 /= 10; while (n > 9) { if (n/p10 != n%10) { return false; } n /= 10; // remove rightmost digit from n p10 /= 10; n %= p10; // remove leftmost digit from n } return true; // single digit integers are palindromic } }

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and x ( n ) a discrete pulse of the form x(n) = Find the convolution y ( n ) = h(n) * x ( n ) .

CHAP. 3]

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Arrays work well for unordered sequences, and even for ordered sequences if they don t change much. But if you want to maintain an ordered list that allows quick insertions and deletions, you should use a linked data structure. This chapter shows how to do that. MAINTAINING AN ORDERED ARRAY 2 outlines how the binary search can find elements very quickly in an array that is sorted. This suggests that we should keep our arrays in sorted order. But inserting new elements in an ordered array is difficult. The main problem is that we have to shift all the larger elements forward to make room for the new element to be placed in its correct ordered position. This can be done by the insert() method shown in Example 3.1. EXAMPLE 3.1 Inserting into an Ordered Array

To evaluate this sum, it will be useful to make a plot of h ( k ) and x ( n - k ) as a function of k as shown in the following figure:

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Note that the amount of overlap between h ( k ) and x ( n - k ) depends on the value of n . For example, if n < 0, there is no overlap, whereas for 0 5 n 5 5 , the two sequences overlap for 0 5 k 5 n . Therefore, in the following, we consider five separate cases.

In Figure 3.5, the index array k[] keeps track of the order of the elements in a[]. The starting index 3 is stored in k[0]. That begins the chain of indexes: k[0] = 3, k[3] = 5, k[5] = 1, k[1] = 4, k[4] = 6, k[6] = 0. The index 0 signals the end of the ordered sequence. The index sequence 0, 3, 5, 1, 4, 6 gives us the data elements in order: a[3] = 22, a[5] = 33, a[1] = 44, a[4] = 55, a[6] = 66. The extra variable free, shown Figure 3.5, saves the index of a free location in both the index array k[] and the data array a[]. The value 7 means that k[7] and a[7] should be used next. The implementation of an index array solves the problem of having to shift segments of array elements back and forth during deletions and insertions. For example, to insert x = 50 in Figure 3.5, we first traverse the sequence to find the index i of the largest element that is less than x: i = 1. Then just follow these three steps:

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