barcode in vb.net Figure 2.10 Analog-to-digital conversion. in Software

Encoding Code 128 in Software Figure 2.10 Analog-to-digital conversion.

Figure 2.10 Analog-to-digital conversion.
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analog conversion circuits are commonly available. The analog signal can be amplified, so that it can drive a transducer, like a loudspeaker, in order to recreate air pressure variations, or sound. The same digital-toanalog converter may, instead, drive a cathode ray tube to create pixels of varying light intensity, according to the binary digit presented to the converter. When the binary digits are stored, they are kept in random access memory circuits, or else recorded as magnetic signals on a hard drive, or as optical pits on a CD-R. The answer to the question: How often do I need to take measurements so as not to miss anything important was answered over 50 years ago by Harry Nyquist and Claude Shannon. It turns out that ears are not sensitive to vibrations of air faster than about 20,000 cycles per second. Nyquist did the math to show that if you sample at twice this rate, i.e., 40,000 cycles per second (or Hz), you are able to reconstruct vibrations of half that frequency. The generalization of this, the Nyquist theorem, says that if you want to sample and reproduce things up to a certain frequency, you need to take measurements at a rate at least twice that frequency. Otherwise, reconstruction is uncertain. You get aliasing. You can fit waves of many shapes and frequencies, not just a single unambiguous one, to the sample points you have. Claude Shannon was interested in how much data could reliably get through a noisy channel of a certain capacity. His work concerned error correction and coding schemes to minimize the effect of introduced noise in a transmission channel. His breakthrough idea was the digital representation of information, sampled at an appropriate rate, as a bit stream of the samples, coded with some redundancy to protect against corruption. These two men are the fathers of digital communications. Without their work, streaming digital media wouldn t be possible.
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Compression
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Compression is a big subject, about which entire books are written. My colleague, Peter Symes, wrote an excellent work entitled Video Compression Demystified, which is a comprehensive treatment of the subject of video compression. Audio compression technology fills other similarly sized books (for example, Markus Erne s book Digital Audio Compression). New compression techniques, being developed all the time, give improvements in picture or sound quality or temporal image quality, for a given amount of bandwidth. Compression is a key enabling technology for streaming media, because it makes efficient use of available band-
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width and, to date, bandwidth has been extremely limited. Without the ability to compress moving images radically, it would currently be impossible to transmit video over the narrowband Internet. Compression is the use of coding techniques to reduce the amount of data used to convey information. Information is in the eye and ear of the beholder, so some of the techniques used in compression exploit these psycho-acoustic and psycho-visual phenomena to disguise the fact that not all the information is delivered (Figure 2.11).
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Figure 2.11 Compression.
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Raw Audio and Video 100110100010 110011101010 100100010110
CompressedAudio and Video
Lossy Compression Engine
Discards information you won t notice is missing
All compression exploits the fact that information has order and patterns. If you can describe the order and patterns, without explicitly transmitting all the bits required to reconstruct the data, given no a priori knowledge, you achieve a reduction in the data required to transmit the original. With compression, it is also vitally important to start with a digital representation of only the information you want to transmit, uncorrupted by noise. If noise is present, bits will be required to represent it. Compression and noise reduction work hand in glove. There are two kinds of compression. One is lossless compression, where you devise a code and a codebook that allows the receiver to exactly decode a digital transmission by looking up coded symbols. It is called lossless compression because the receiver can recover an exact replica of the original digital representation, even though a reduced data stream was actually transmitted. Lossy compression, on the other hand, exploits perceptual anomalies of the human nervous system to send a good-enough digital represen-
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