The Scientist and Engineer's Guide to Digital Signal Processing - Steven W. Smith.pdf

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CHAPTER
1
The Breadth and Depth of DSP
Digital Signal Processing is one of the most powerful technologies that will shape science and
engineering in the twenty-first century. Revolutionary changes have already been made in a broad
range of fields: communications, medical imaging, radar & sonar, high fidelity music
reproduction, and oil prospecting, to name just a few. Each of these areas has developed a deep
DSP technology, with its own algorithms, mathematics, and specialized techniques. This
combination of breath and depth makes it impossible for any one individual to master all of the
DSP technology that has been developed. DSP education involves two tasks: learning general
concepts that apply to the field as a whole, and learning specialized techniques for your particular
area of interest. This chapter starts our journey into the world of Digital Signal Processing by
describing the dramatic effect that DSP has made in several diverse fields. The revolution has
begun.
The Roots of DSP
Digital Signal Processing is distinguished from other areas in computer science
by the unique type of data it uses: signals . In most cases, these signals
originate as sensory data from the real world: seismic vibrations, visual images,
sound waves, etc. DSP is the mathematics, the algorithms, and the techniques
used to manipulate these signals after they have been converted into a digital
form. This includes a wide variety of goals, such as: enhancement of visual
images, recognition and generation of speech, compression of data for storage
and transmission, etc. Suppose we attach an analog-to-digital converter to a
computer and use it to acquire a chunk of real world data. DSP answers the
question: What next ?
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
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The Scientist and Engineer's Guide to Digital Signal Processing
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 was
suddenly 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
-Space photograph enhancement
-Data compression
-Intelligent sensory analysis by
remote space probes
Space
-Diagnostic imaging (CT, MRI,
ultrasound, and others)
-Electrocardiogram analysis
-Medical image storage/retrieval
Medical
-Image and sound compression
for multimedia presentation
-Movie special effects
-Video conference calling
Commercial
DSP
-Voice and data compression
-Echo reduction
-Signal multiplexing
-Filtering
Telephone
-Radar
-Sonar
-Ordnance guidance
-Secure communication
Military
-Oil and mineral prospecting
-Process monitoring & control
-Nondestructive testing
-CAD and design tools
Industrial
-Earthquake recording & analysis
-Data acquisition
-Spectral analysis
-Simulation and modeling
Scientific
FIGURE 1-1
DSP has revolutionized many areas in science and engineering. A
few of these diverse applications are shown here.
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Chapter 1- The Breadth and Depth of DSP
3
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.
Communication
Theory
Digital
Signal
Processing
Numerical
Analysis
Probability
and Statistics
Analog
Signal
Processing
Analog
Electronics
Digital
Electronics
Decision
Theory
FIGURE 1-2
Digital Signal Processing has fuzzy and overlapping borders with many other
areas of science, engineering and mathematics.
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The Scientist and Engineer's Guide to Digital Signal Processing
Telecommunications
Telecommunications is about transferring information from one location to
another. This includes many forms of information: telephone conversations,
television signals, computer files, and other types of data. To transfer the
information, you need a channel between the two locations. This may be
a wire pair, radio signal, optical fiber, etc. Telecommunications companies
receive payment for transferring their customer's information, while they
must pay to establish and maintain the channel. The financial bottom line
is simple: the more information they can pass through a single channel, the
more money they make. DSP has revolutionized the telecommunications
industry in many areas: signaling tone generation and detection, frequency
band shifting, filtering to remove power line hum, etc. Three specific
examples from the telephone network will be discussed here: multiplexing,
compression, and echo control.
Multiplexing
There are approximately one billion telephones in the world. At the press of
a few buttons, switching networks allow any one of these to be connected to
any other in only a few seconds. The immensity of this task is mind boggling!
Until the 1960s, a connection between two telephones required passing the
analog voice signals through mechanical switches and amplifiers. One
connection required one pair of wires. In comparison, DSP converts audio
signals into a stream of serial digital data. Since bits can be easily
intertwined and later separated, many telephone conversations can be
transmitted on a single channel. For example, a telephone standard known
as the T-carrier system can simultaneously transmit 24 voice signals. Each
voice signal is sampled 8000 times per second using an 8 bit companded
(logarithmic compressed) analog-to-digital conversion. This results in each
voice signal being represented as 64,000 bits/sec, and all 24 channels being
contained in 1.544 megabits/sec. This signal can be transmitted about 6000
feet using ordinary telephone lines of 22 gauge copper wire, a typical
interconnection distance. The financial advantage of digital transmission
is enormous. Wire and analog switches are expensive; digital logic gates
are cheap.
Compression
When a voice signal is digitized at 8000 samples/sec, most of the digital
information is redundant . That is, the information carried by any one
sample is largely duplicated by the neighboring samples. Dozens of DSP
algorithms have been developed to convert digitized voice signals into data
streams that require fewer bits/sec. These are called data compression
algorithms. Matching uncompression algorithms are used to restore the
signal to its original form. These algorithms vary in the amount of
compression achieved and the resulting sound quality. In general, reducing the
data rate from 64 kilobits/sec to 32 kilobits/sec results in no loss of sound
quality. When compressed to a data rate of 8 kilobits/sec, the sound is
noticeably affected, but still usable for long distance telephone networks.
The highest achievable compression is about 2 kilobits/sec, resulting in
Chapter 1- The Breadth and Depth of DSP
5
sound that is highly distorted, but usable for some applications such as military
and undersea communications.
Echo control
Echoes are a serious problem in long distance telephone connections.
When you speak into a telephone, a signal representing your voice travels
to the connecting receiver, where a portion of it returns as an echo. If the
connection is within a few hundred miles, the elapsed time for receiving the
echo is only a few milliseconds. The human ear is accustomed to hearing
echoes with these small time delays, and the connection sounds quite
normal. As the distance becomes larger, the echo becomes increasingly
noticeable and irritating. The delay can be several hundred milliseconds
for intercontinental communications, and is particularly objectionable.
Digital Signal Processing attacks this type of problem by measuring the
returned signal and generating an appropriate antisignal to cancel the
offending echo. This same technique allows speakerphone users to hear
and speak at the same time without fighting audio feedback (squealing).
It can also be used to reduce environmental noise by canceling it with
digitally generated antinoise .
Audio Processing
The two principal human senses are vision and hearing. Correspondingly,
much of DSP is related to image and audio processing. People listen to
both music and speech . DSP has made revolutionary changes in both
these areas.
Music
The path leading from the musician's microphone to the audiophile's speaker is
remarkably long. Digital data representation is important to prevent the
degradation commonly associated with analog storage and manipulation. This
is very familiar to anyone who has compared the musical quality of cassette
tapes with compact disks. In a typical scenario, a musical piece is recorded in
a sound studio on multiple channels or tracks. In some cases, this even involves
recording individual instruments and singers separately. This is done to give
the sound engineer greater flexibility in creating the final product. The
complex process of combining the individual tracks into a final product is
called mix down . DSP can provide several important functions during mix
down, including: filtering, signal addition and subtraction, signal editing, etc.
One of the most interesting DSP applications in music preparation is
artificial reverberation . If the individual channels are simply added together,
the resulting piece sounds frail and diluted, much as if the musicians were
playing outdoors. This is because listeners are greatly influenced by the echo
or reverberation content of the music, which is usually minimized in the sound
studio. DSP allows artificial echoes and reverberation to be added during
mix down to simulate various ideal listening environments. Echoes with
delays of a few hundred milliseconds give the impression of cathedral like
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