Computer Science
Data Encoding
Data encoding is the process of converting information from one format to another for efficient transmission or storage. It involves transforming data into a code that can be easily interpreted by a computer or other electronic device. This process is essential for ensuring that data is accurately and efficiently transmitted and stored.
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3 Key excerpts on "Data Encoding"
- Bilal M. Ayyub, George J. Klir(Authors)
- 2006(Publication Date)
- Chapman and Hall/CRC(Publisher)
67 2 Encoding Data and Expressing Information 2.1 INTRODUCTION This chapter provides background information, mathematical methods, and analyt-ical tools that can be used to encode data and express information for the purpose of creating some structure or order needed to solve problems in engineering and the sciences. The various ways of encoding and expressing data and information are important components of uncertainty modeling and analysis, and sometimes are termed as formalized languages . Encoding data also includes the expression of an opinion of an expert that can be defined in a numeric or nonnumeric manner, including a representation in natural language or a picture, or a figure representing or symbolizing the opinion. The expression in this case might be sensitive to the choice of a particular word, phrase, sentence, symbol, or picture. It can also include a show of feeling or character. It can be in the form of a symbol or a set of symbols expressing some mathematical or analytical relationship, as a quantity or operation. In this chapter, we present formalized languages and selected functions of formalized languages that include the fundamentals of classical set theory, fuzzy sets, generalized measures, rough sets, and gray systems. These languages can be used to express and encode data and information. Basic operations for these theories are defined and demonstrated. Operations relating to these theories are presented for the purpose of combining collected information or data for solving problems or system modeling. Relations and operations can be used to express and combine collected information. In addition, methods for dealing with system complexity and simplification are provided in this chapter. Examples are used in this chapter to demonstrate the various methods and concepts. The level of coverage detail of a particular method was set based on the maturity and potentials of the method.
eBook - PDFComputer Networks ISE
A Systems Approach
- Larry L. Peterson, Bruce S. Davie(Authors)
- 2007(Publication Date)
- Morgan Kaufmann(Publisher)
Section 7.1 describes var-ious encodings of traditional computer data, such as integers, floating-point numbers, character strings, arrays, and structures. Well-established formats also exist for multime-dia data: Video, for example, is typically transmitted in Moving Picture Experts Group (MPEG) format, and still images are usually transmitted in Joint Photographic Experts Group (JPEG) format or graphical interchange format (GIF). Because these formats 542 7 are primarily noteworthy for the compression algorithms they use, we consider them in that context in Section 7.2. The second main concern of this chapter, the efficiency of the encoding, has a rich history, dating back to Shannon’s pioneer work on information theory in the 1940s. In effect, there are two opposing forces at work here. In one direction, you would like as much redundancy in the data as possible so that the receiver is able to extract the right data even if errors are introduced into the message. The error detection and correcting codes we saw in Section 2.4 add redundant information to messages for exactly this purpose. In the other direction, we would like to remove as much redundancy from the data as possible so that we may encode it in as few bits as possible. This is the goal of data compression , which we discuss in Section 7.2. Compression is important to the designers of networks for a wealth of reasons, not just because we rarely find ourselves with an abundance of bandwidth everywhere in the network. For exam-ple, the way we design a compression algorithm affects our sensi-tivity to lost or delayed data, and thus may influence the design of resource allocation mechanisms and end-to-end protocols. Con-versely, if the underlying network is unable to guarantee a fixed amount of bandwidth for the duration of a videoconference, we may choose to design compression algorithms that can adapt to changing network conditions.
eBook - PDF- Christine Mullings, Stephanie Kenna, Marilyn Deegan, Seamus Ross, Christine Mullings, Stephanie Kenna, Marilyn Deegan, Seamus Ross(Authors)
- 2019(Publication Date)
- De Gruyter Saur(Publisher)
The process is not so very different in principle from what a human reader must go through to learn a language, understand that certain kinds of marks made on paper (e.g. written or printed words) represent that language, appreciate that the organization of both the marks and pieces of paper conveys additional information about relatedness (e.g. a linear narrative), and so forth. By the time most people come to use a computer they have forgotten just what a sophisticated act reading actually is—and the tendency to attribute human-like knowledge and intelligence to dumb boxes of electronic circuitry only makes it more frustrating when they will not do what is required. 1 In order to get a computer to do something useful with a text, it needs to be loaded into the computer in a format that can be understood and processed. In an ideal world, there would be a common format (i.e. internal encoding of a text) which every computer and every software application could understand and process in the same way. Unfortunately, we do not live in an ideal world—although, as we shall see, standards do exist for encoding texts independently of particular computers or applications. Text Encoding, Analysis, and Retrieval 5 Preparation The assumption from this point on is that you have identified an existing text (i.e. a particular printed edition, a collection of manuscripts, etc.) which you wish to process with the aid of a computer. There are three common methods of getting text into a computer: scanning, keying, and reusing existing electronic text. Which of these you choose will depend on a combination of factors, such as the form in which the text currently exists (printed paper, manuscript, stone inscription, electronic file), the resources available to you (time, money, assistance, equipment), and your previous experience.
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