Alogrithm Design According to Weiss, an algorithm is

According to Weiss, an algorithm is a "clearly specified set of simple instructions to be followed to solve a problem." The problem can be in any field, although algorithms are most often associated with computer science, and the key to a successful algorithm is determining its relevance and accuracy to the problem at hand. Even algorithms which are relevant and which accurately solve a problem may be deemed inappropriate if they require too much time or other resources. This research examines why algorithm design is important to the biomedical field, and considers five commonly used approaches to algorithms and their relevance to the field of clinical engineering.

Everyone uses algorithms in performing day-to-day activities. The algorithm is merely the set of instructions that we use to solve problems. In day-to-day existence, the problem of not having enough funds in a checking account is solved by depositing a check into the account. The algorithm for doing this might involve driving to the local branch, endorsing the check, choosing the automated teller machine over actually going into the bank, and so on. The algorithm does not spell out the exact way in which the various instructions are performed, but it outlines the steps that need to be accomplished.

The same is true with algorithms as applied to computers. Such algorithms do not lay out the exact code that is required to complete a task, but they do put forth the tasks that need t

r sorting algorithm which uses the divide and conquer algorithm technique is that of quicksort. Similar to mergesort, quicksort depends on a pivot point, selected at random. The data on either side of the pivot point are sorted and then brought back together. Key to this algorithm is the selection of the pivot point. While at first this could appear a trivial problem, it is the basis for the entire algorithm and thus has severe ramifications. If the first point is chosen, for example, there can be problems, particularly when the data are presorted. The result can be that too many points fall on one side of the pivot point, thus reducing the gains that would otherwise be associated with this technique. Since much data is already presorted (at least to some degree), this intuitive approach to choosing a pivot point can be, and often is, highly detrimental to the technique's effectiveness. Another technique for choosing the pivot point is to do so at random. This can be done with a random number generator and is likely to provide a generally acceptable pivot point on a regular basis. However, random number generators are themselves resource intensive, and the trade-off between the desirability of a random pivot point and

Category: Science - A