China
Africa
Explore chapters and articles related to this topic
Number Systems and Codes
Published in Sajjan G. Shiva, Introduction to Logic Design, 2018
Errors occur during digital data transmission as a result of the external noise introduced by the medium of transmission. For example, if a digital system uses BCD code for data representation and if an error occurs in the LSB position of the data 0010, the resulting data will be 0011. Because 0011 is a valid code word, the receiving device assumes that the data are not in error. To guard against such erroneous interpretations of data, several error detection and correction schemes have been devised. As the names imply, an error detection scheme simply detects that an error has occurred, while an error correction scheme corrects the errors. We will describe a simple error detection scheme using parity checking here. For information on more elaborate schemes, such as Cyclic Redundancy Check (CRC), Check sums, and XModem protocols, see the books by Kohavi and Ercegovac and Lang listed in the reference section at the end of the chapter.
Error correction
Published in John Watkinson, The Art of Digital Audio, 2013
Error correction works by adding some bits to the data which are calculated from the data. This creates an entity called a codeword which spans a greater length of time than one bit alone. In recording, the requirement is to spread the codeword over an adequate area of the medium. The statistics of noise means that whilst one bit may be lost in a codeword, the loss of the rest of the codeword because of noise is highly improbable. As will be described later in this chapter, codewords are designed to be able to correct totally a finite number of corrupted bits. The greater the timespan or area over which the coding is performed, the greater will be the reliability achieved, although this does mean that greater encoding and decoding delays will have to be accepted.
Digital coding principles
Published in John Watkinson, An Introduction to Digital Video, 2012
Error correction works by adding some bits to the data which are calculated from the data. This creates an entity called a codeword which spans a greater length of time than one bit alone. The statistics of noise means that whilst one bit may be lost in a codeword, the loss of the rest of the codeword because of noise is highly improbable. As will be described later in this chapter, codewords are designed to be able to correct totally a finite number of corrupted bits. The greater the timespan over which the coding is performed, or, on a recording medium, the greater area over which the coding is performed, the greater will be the reliability achieved, although this does mean that an encoding delay will be experienced on recording, and a similar or greater decoding delay on reproduction.
Performance of Soft Viterbi Decoder enhanced with Non-Transmittable Codewords for storage media
Published in Cogent Engineering, 2018
Kilavo Hassan, Kisangiri Michael, Salehe I. Mrutu
The demand for digital data storage media increases every day and it is estimated that over 90% of all the digital data produced in the world is being stored in hard disk. Sometimes, errors occur in storage media and hence; causing data retrieving difficulties that lead to data loss. Error control in storage media rely upon error correction algorithms to guarantee information retrieval. Reed Solomon (RS) code is the dominant algorithm for errors correcting in storage media. However, recent studies show that there still exist challenges in retrieving data from storage media. This research is among the efforts to design more powerful and effective error correction algorithms. In this study, Soft Viterbi Algorithm Decoder enhanced with Non-Transmittable Codewords (SVAD-NTCs) is proposed. The experiment results for error correction in storage media show that, SVAD-NTCs perform better than RS.