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原来数字信号处理“魔盒”是这样打开的

发布时间:2020-05-29 发布时间:
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数字信号处理与计算机科学中的其他领域有很大区别,因为它所使用的是特别的数据类型:信号。在大多数情况下,这些信号来自于对真实世界的感知数据,例如:地震振动,视觉图像,声波等等。数字信号处理是使用数学、算法以及一些技巧来处理被转换成数字形式的信号。这数字信号处理有各种各样的易用,如:视觉图像增强、语音识别与语音生成、数据的压缩存储和传输等。如果我们连接一个模拟—数字转换器到一台计算机上,并用它来获取一组真实世界的数据。数字信号处理会告诉你接下来要做什么?

 

The roots of DSP are in the 1960s and 1970s when digital computers first became available. Computers were expensive during this era, and DSP was limited to only a few critical applications. Pioneering efforts were made in four key areas: radar & sonar, where national security was at risk; oil exploration, where large amounts of money could be made; space exploration, where the data are irreplaceable; and medical imaging, where lives could be saved.

 

The personal computer revolution of the 1980s and 1990s caused DSP to explode with new applications. Rather than being motivated by military and government needs, DSP was suddenly driven by the commercial marketplace. Anyone who thought they could make money in the rapidly expanding field wassuddenly a DSP vendor. DSP reached the public in such products as: mobile telephones, compact disc players, and electronic voice mail. Figure 1-1 illustrates a few of these varied applications.


This technological revolution occurred from the top-down. In the early 1980s, DSP was taught as a graduate level course in electrical engineering. A decade later, DSP had become a standard part of the undergraduate curriculum. Today, DSP is a basic skill needed by scientists and engineers

 

FIGURE 1-1
DSP has revolutionized many areas in science and engineering. A
few of these diverse applications are shown here.

 

in many fields. As an analogy, DSP can be compared to a previous technological revolution: electronics. While still the realm of electrical engineering, nearly every scientist and engineer has some background in basic circuit design. Without it, they would be lost in the technological world. DSP has the same future.


This recent history is more than a curiosity; it has a tremendous impact on your ability to learn and use DSP. Suppose you encounter a DSP problem, and turn to textbooks or other publications to find a solution. What you will typically find is page after page of equations, obscure mathematical symbols, and unfamiliar terminology. It's a nightmare! Much of the DSP literature is baffling even to those experienced in the field. It's not that there is anything wrong with this material, it is just intended for a very specialized audience.


State-of-the-art researchers need this kind of detailed mathematics to understand the theoretical implications of the work. A basic premise of this book is that most practical DSP techniques can be
learned and used without the traditional barriers of detailed mathematics and theory. The Scientist and Engineer’s Guide to Digital Signal Processing is written for those who want to use DSP as a tool, not a new career.

 

The remainder of this chapter illustrates areas where DSP has produced revolutionary changes. As you go through each application, notice that DSP is very interdisciplinary, relying on the technical work in many adjacent fields. As Fig. 1-2 suggests, the borders between DSP and other technical disciplines are not sharp and well defined, but rather fuzzy and overlapping. If you want to specialize in DSP, these are the allied areas you will also need to study.

 

FIGURE 1-2
Digital Signal Processing has fuzzy and overlapping borders with many other
areas of science, engineering and mathematics.

 

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