Results 251 to 260 of about 25,195 (291)
Some of the next articles are maybe not open access.
1994
For a collection of data objects, we have discussed some data organizing techniques that use array, linked list, stack, queue, tree, and graph objects (to be discussed later). Such basic operations as insertion, deletion, and even searching for these objects were discussed and implemented. A wise selection of one or more such objects for an application
Saumyendra Sengupta +1 more
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For a collection of data objects, we have discussed some data organizing techniques that use array, linked list, stack, queue, tree, and graph objects (to be discussed later). Such basic operations as insertion, deletion, and even searching for these objects were discussed and implemented. A wise selection of one or more such objects for an application
Saumyendra Sengupta +1 more
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2020
Let a1, . . . ,an be a finite sequence. The elements of the sequence should be elements of an ordered set. The order relation is ≤.
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Let a1, . . . ,an be a finite sequence. The elements of the sequence should be elements of an ordered set. The order relation is ≤.
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2020
As its title suggests, this chapter also has two parts. The first provides the reader with an introduction to searching – a very important aspect of computing. It introduces the sequential search and describes how to do it in an array as well as in a linked list.
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As its title suggests, this chapter also has two parts. The first provides the reader with an introduction to searching – a very important aspect of computing. It introduces the sequential search and describes how to do it in an array as well as in a linked list.
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2012
This chapter explores two very practical problems: searching and sorting. We consider Linear Search and (two versions of) Binary Search. Binary trees are used to describe the search process. Binary search is much, much better but requires sorted input. We give examples of several sorting strategies: selection sorts, exchange sorts, and partition sorts.
Tom Jenkyns, Ben Stephenson
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This chapter explores two very practical problems: searching and sorting. We consider Linear Search and (two versions of) Binary Search. Binary trees are used to describe the search process. Binary search is much, much better but requires sorted input. We give examples of several sorting strategies: selection sorts, exchange sorts, and partition sorts.
Tom Jenkyns, Ben Stephenson
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Searching in a Sorted Linked List
2018 International Conference on Information Technology (ICIT), 2018Let A be the array of n integers in {0, 1, …, n-1}. A tree is constructed in O(nloglogm/p+loglogm) time with p processors based on the trie with all the given integers. Additional nodes (O(nloglogm) of them) are added to the tree. After the tree is construct we can, for any given integer, find the predecessor and successor of this integer, insert or ...
Hemasree Koganti, Yijie Han
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1993
Abstract In this section we will discuss some important parallel sorting algorithm. We have already seen one sorting algorithm at the end of§ 2 in chapter II. That algorithm sorted n numbers in time O(lg2n) using 0( n) processors. The theoretical lower bound in time for sorting n numbers is O(lg n) (since this many comparisons must be
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Abstract In this section we will discuss some important parallel sorting algorithm. We have already seen one sorting algorithm at the end of§ 2 in chapter II. That algorithm sorted n numbers in time O(lg2n) using 0( n) processors. The theoretical lower bound in time for sorting n numbers is O(lg n) (since this many comparisons must be
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1992
A new neural network parallel algorithm for sorting problems is introduced in this Chapter. The proposed algorithm using 0(n2) processors requires two and only two steps, not depending on the problem size, while the conventional parallel sorting algorithm using O(n) processors proposed by Leighton needs the computation time 0(log n).
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A new neural network parallel algorithm for sorting problems is introduced in this Chapter. The proposed algorithm using 0(n2) processors requires two and only two steps, not depending on the problem size, while the conventional parallel sorting algorithm using O(n) processors proposed by Leighton needs the computation time 0(log n).
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2017
Many efficient algorithms are based on sorting the input data, because sorting often makes solving the problem easier. This chapter discusses the theory and practice of sorting as an algorithm design tool. Section 4.1 first discusses three important sorting algorithms: bubble sort, merge sort, and counting sort. After this, we will learn how to use the
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Many efficient algorithms are based on sorting the input data, because sorting often makes solving the problem easier. This chapter discusses the theory and practice of sorting as an algorithm design tool. Section 4.1 first discusses three important sorting algorithms: bubble sort, merge sort, and counting sort. After this, we will learn how to use the
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2017
The current English meaning of the terms "searching" and "sorting" also holds good in computer science. Sometimes, this is not the case. For example, the current English meaning of the terms "root," "garbage or "tree" is very different from their meaning in computer science.
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The current English meaning of the terms "searching" and "sorting" also holds good in computer science. Sometimes, this is not the case. For example, the current English meaning of the terms "root," "garbage or "tree" is very different from their meaning in computer science.
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Localized search in sorted lists
Proceedings of the thirteenth annual ACM symposium on Theory of computing - STOC '81, 1981It is well known that every one of the set operations insert, delete and member can be performed in O(log n) steps, where n is the number of elements currently in the set. Here we implement these operations and a move operation for a sorted list with f fingers (points of reference) established on the list.
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