Different Sorting Algorithm’s Comparison based Upon the Time Complexity

Time-constrained sorting-a comparison of different algorithms

The designers of real-time systems try to avoid a poor utilization of hardware by assigning only the absolutely necessary time budget to each task. In certain cases it is also acceptable to cut the time quantum assigned to a task below its worst-case needs, provided (a) a high percentage of executions complete within this quantum and (b) the quality of the aborted computations is su cient for f...

Improved Average Complexity for Comparison-Based Sorting

This paper studies the average complexity on the number of comparisons for sorting algorithms. Its information-theoretic lower bound is n lg n− 1.4427n+O(log n). For many efficient algorithms, the first n lg n term is easy to achieve and our focus is on the (negative) constant factor of the linear term. The current best value is −1.3999 for the MergeInsertion sort. Our new value is −1.4106, nar...

Lower bound on comparison-based sorting algorithms

Spike sorting based upon machine learning algorithms (SOMA).

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would on...

A Comparison of Parallel Sorting Algorithms on Different Architectures

In this paper, we present a comparative performance evaluation of three different parallel sorting algorithms: bitonic sort, sample sort, and parallel radix sort. In order to study the interaction between the algorithms and the architecture, we implemented all the algorithms on three different architectures: a MasPar MP1202, a mesh-connected computer with 2048 processing elements; an nCUBE 2, a...