must be sam 7.26. The sampling theorem, as we have derived it, pled at a rate greater than its bandwidth (or equivalently, a rate greater than twice its highest frequency). This implies that if x(1) has a spectrum as indicated in Figure P7.26(a) then x(1) must be sampled at a rate greater than 2002. However, since the signal has most of its energy concentrated in a narrow band, it would seem reason- able to expect that a sampling rate lower than twice the highest frequency could be as a bandpass signal. There are a variety of techniques for sampling such signals, used. A signal whose energy is concentrated in a frequency band is often referred to generally referred to as bandpass-sampling techniques. x(t) ... X(jw) лід -W₂ -w₁ W₁ W₂ (a) wo ** p(t) = 8(t-nT) -W₂ Xp (t) H(jw) H(jw) p(t) iu (b) W ... wp w x, (t) Figure P7.26
Quantization and Resolution
Quantization is a methodology of carrying out signal modulation by the process of mapping input values from an infinitely long set of continuous values to a smaller set of finite values. Quantization forms the basic algorithm for lossy compression algorithms and represents a given analog signal into digital signals. In other words, these algorithms form the base of an analog-to-digital converter. Devices that process the algorithm of quantization are known as a quantizer. These devices aid in rounding off (approximation) the errors of an input function called the quantized value.
Probability of Error
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