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In the context of Digital signal processing (DSP), a digital signal is a discrete-time signal for which not only the time but also the amplitude has discrete values; in other words, its samples take on only values from a discrete set (a countable set that can be mapped one-to-one to a subset of integers). If that discrete set is finite, the discrete values can be represented with digital words of a finite width. Most commonly, these discrete values are represented as fixed-point words (either proportional to the waveform values or companded) or floating-point words. The process of analog-to-digital conversion produces a digital signal. It can be thought of as two steps: (1) sampling, which produces a continuous-valued discrete-time signal, and (2) quantization, which replaces each sample value by an approximation selected from a given discrete set (for example by truncating or rounding). It can be shown that for signal frequencies strictly below the Nyquist limit that the original continuous-valued continuous-time signal can be almost perfectly reconstructed, down to the (often very low) limit set by the quantisation. Common practical digital signals are represented as 8-bit (256 levels), 16-bit (65,536 levels), 32-bit (4.3 billion levels). But the number of quantization levels is not limited to powers of two. == See also == *Nyquist–Shannon sampling theorem *Whittaker–Shannon interpolation formula 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Digital signal (signal processing)」の詳細全文を読む スポンサード リンク
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