科技英语 5数字信号处理器原文与翻译

Words and Expressions
follow v. 遵循 memory n. 存储器
register n. 寄存器 access v. 访问
overlap v. 重叠 pipelining n. 流水线操作
multiplier n. 乘法器 accumulator n. 累加器
shifter n. 移位器 reference n. 寻址
mantissa n. 尾数 exponent n. 指数
cycle n. 机器周期 customize v. 定制，用户化
package v. 封装
digital signal processor 数字信号处理器
von Neumann architecture 冯·诺伊曼结构
shared single memory 单一共享存储器
program instruction 程序指令
harvard architecture 哈佛结构
fetch from 从…获取
circular buffer 循环缓冲区，环形缓冲区
address generator 地址产生器
fixed point 定点
floating point 浮点
binary point 二进制小数点
available precision 可用精度
dynamic range 动态范围
scale range 量程
smallest Resolvable Difference 最小分辨率
scientific notation 科学计数法
assembly language 汇编语言
multi-function instructions 多功能指令
parallel architecture 并行结构
looping scheme 循环机制
sampling frequency 采样频率
calculation-intensive algorithm 运算密集型算法

on-chip memory 片内存储器
well-matched 非常匹配
software tools 软件开发工具
low level programming language 低级编程语言
high level programming language 高级编程语言
third party software 第三方软件
board level product 板级产品
data register 数据寄存器
ALU=Arithmetic Logical Unit 运算逻辑单元
program sequencer 程序定序器
peripheral sections 外设
single integrated circuit 单片集成电路
cellular telephone 蜂窝电话
printed circuit board 印刷电路板
licensing agreement 专利使用权转让协定
custom devices 定制器件
extra memory 附加存储器
stand alone 单机
third party developer 第三方开发商
multimedia operations 多媒体操作
merged into 融合




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Unit 5 Digital Signal Processors


Digital signal processing tasks can be performed by all processors. Specialized digital signal
processors (DSPs), however, perform these tasks most efficiently and most quickly. While traditional
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processors follow the Von Neumann architecture model, which assumes a shared single memory to
be used for both program instructions and data, DSPs use the Harvard or modified Harvard
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architecture , which includes multiple program and data memories, along with multiple buses to access
them. This arrangement means that much less waiting is required when instructions or numbers are
fetched from memory. In fact at least one of each can be fetched simultaneously. Such overlapping of
tasks is called pipelining. In addition to multiple memories and buses, all DSPs have fast multipliers,
accumulators, and shifters, and many have hardware support for circular buffers. Address generators
can speed up accesses to memory locations referenced by registers.
DSPs are available in two major classes: fixed point and floating point. The fixed point class
represents real numbers in a fixed number of bits. The position of the binary point (similar to the decimal
point) can be controlled by the programmer, and determines the range of numbers that can be represented.
As the range increases, though, the available precision goes down, since fewer bits lie to the right of the
binary point. In 16 bits, the formats 16.0, 15.1, 14.2, 13.3, 12.4, 11.5, 10.6, 9.7, 8.8, 7.9, 6.10, 5.11, 4.12,
3.13, 2.14, and 1.15 are possible. The dynamic range, calculated as 20log (Full Scale RangeSmallest
Resolvable Difference), remains the same for all 16-bit formats, 20log
2
= 96.3 dB.
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Figure 6.3 Van Neumann architecture

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Figure 6.4 Harvard architecture
Floating point DSPs represent real numbers using a mantissa and an exponent, similar to scientific
notation: Many combine mantissa and exponent into a 32-bit number. The dynamic range for floating
point devices is calculated from the largest and smallest multipliers
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, where E is the exponent. Thus, for
a representation that uses 24 bits for the mantissa and 8 bits for the signed exponent, the dynamic range is
20 log (
2
127
E
2
?128
) = 1535.3 dB. A large dynamic range means the system has great power to represent
a wide range of input signals, from very small to very large.
Assembly language is the command language for DSPs. DSPs often have specialized instructions
that make programming for common DSP tasks more convenient and more efficient. For example, most
DSPs offer multi-function instructions that exploit their parallel architecture. Other constructs that are
frequently offered are efficient looping schemes, since so many DSP operations involve a great deal of
repetition.
Choosing a DSP for a particular application is not always easy. The first decision is on whether to
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choose a fixed point or a floating point device. Generally, fixed point devices are cheaper and quicker,
but floating point devices are more convenient to program and more suited to calculation-intensive
algorithms. Second, the data width of the DSP determines how accurately it can represent numbers. Speed
is another issue, not only how many cycles occur in each second, but also how many instructions execute
in each cycle and how much work each of these instructions accomplishes. One way to assess the
minimum requirements for the DSP is to estimate how many instructions must be executed for each
received sample. When this number is multiplied by the sampling frequency, the minimum required
number of instructions per second is obtained.
The specific hardware and software features offered by a particular DSP can make one choice better
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than another, as can the amount of on-chip memory available. Sometimes DSPs are chosen because

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well-matched supporting hardware, particularly AD and DA converters, is obtainable. Frequently, the
quality and convenience of the software tools, for both low level and high level programming languages,
are also major factors, as is the availability of third party software. As always, cost is a factor. In fact,
quite often, the DSP that is fastest and offers the most features, but also fits the budget, is the one
selected.
DSPs can be purchased in three forms, as a core, as a processor, and as a board level product. In
DSP, the term
the data registers, multiplier, ALU, address generator, and program sequencer. A complete processor
requires combining the core with memory and interfaces to the outside world. While the core and these
peripheral sections are designed separately, they will be fabricated on the same piece of silicon, making
the processor a single integrated circuit.
Suppose you build cellular telephones and want to include a DSP in the design. You will probably
want to purchase the DSP as a processor, that is, an integrated circuit that contains the core, memory and
other internal features. To incorporate this IC in your product, you have to design a printed circuit board
where it will be soldered in next to your other electronics. This is the most common way that DSPs are
used.
Now, suppose the company you work for manufactures its own integrated circuits. In this case, you
might not want the entire processor, just the design of the core. After completing the appropriate licensing
agreement, you can start making chips that are highly customized to your particular application. This
gives you the flexibility of selecting how much memory is included, how the chip receives and transmits
data, how it is packaged, and so on. Custom devices of this type are an increasingly important
segment of the DSP marketplace.
There are several dozen companies that will sell you DSPs already mounted on a printed circuit board.
These have such features as extra memory, AD and DA converters, EPROM sockets, multiple
processors on the same board, and so on. While some of these boards are intended to be used as stand
alone computers, most are configured to be plugged into a host, such as a personal computer. Companies
that make these types of boards are called Third Party Developers. The best way to find them is to ask
the manufacturer of the DSP you want to use. Look at the DSP manufacturer's website; if you don't find a
list there, send them an e-mail. They will be more than happy to tell you who are using their products and
how to contact them.
Keep in mind that the distinction between DSPs and other microprocessors is not always a clear line.
For instance, look at how Intel describes the MMX technology addition to its Pentium processor:
engineers have added 57 powerful new instructions specifically designed to manipulate and process video,
audio and graphical data efficiently. These instructions are oriented to the highly parallel, repetitive

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sequences often found in multimedia operations.
In the future, we will undoubtedly see more DSP-like functions merged into traditional
microprocessors and microcontrollers. The Internet and other multimedia applications are a strong driving
force for these changes. These applications are expanding so rapidly, in twenty years it is very possible
that the Digital Signal Processor may be the


Notes
1. “冯·诺伊曼结构”取名字美国杰出的数学家—约翰·冯·诺伊曼（John Von
Neumann ,1903~1957）。他引导了20世纪初许多重大数学发现。他的主要成就包括：提出了存储程
序 计算机（stored program computer）的概念、对量子力学的数学公式化及在原子弹方面的工作。
2． “哈佛结构”取名自20世纪40年代 Howard Aiken (1900~1973)领导的在哈佛大学（Harvard
University）做的研究工作。
3． 本句可译为：首先要决定的是选择定点器件还是浮点器件。
4. 本句可译为：和片 内可用存储器大小能做出更佳选择的判断一样，特定数字信号处理器所提供
的软硬件特点会使一个选择优 于另一个选择。

数字信号处理器

所有处理器都可以完成数字 信号处理的任务。然而，专用数字信号处理器完成数字信号任务的
效率和速度都是最好的。传统的处理器 遵循冯·诺伊曼模型，该模型采用一个单一的共享存储器，
同时存储程序指令和数据；而数字信号处理器 使用的是哈佛结构或改进哈佛结构，该结构包含多个
程序和数据存储器以及访问这些存储器的多套总线。 这样安排就意味着从存储器取指令或取数据所
需的等待时间要少得多。实际上，至少可以同时取得一条指 令和一个数据。这种任务的重叠称做流
水线。除了多存储器和多总线之外，所有数字信号处理器都有快速 的乘法器、累加器和移位器，而
且许多数字信号处理器都有支持循环缓冲区的硬件。地址产生器可以加速 对寄存器寻址的存储器访
问。
数字信号处理器分为定点和浮点两大类。定点数字信号 处理器使用固定的比特数来代表实数。
二进制小数点的位置可以由编程人员决定，这个位置决定了可以表 示的实数范围。可用精度要随着
表示范围的增加而下降，因而二进制小数点右边的比特数减少了。在16 位数据中，可能出现的格式
有16.0，15.1，14.2，13.3，12.4，11.5，10. 6，9.7，8.8，7.9，6.10，5.11，4.12，3.13，2.14和1.15。
所有 16位定点数据格式的动态范围都是一样的，都是
20log2
16
?96.3dB< br>。动态范围的计算方法为：
20log
（满量程范围最小可分辨差别）。
浮点数字信号处理器使用尾数和指数来表示实数，这种方法和科学计数法很相似—将尾数和指
数组合成一 个32位数。浮点器件的动态范围是用
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的最大值和最小值进行计算的，此处E是指数。
这样，对于24位尾数和8位有符号指数的表示方法而言，动态范围是
20log2
127< br>2
?128
?1535.3dB
。
大的动态范围意味着系统具备更大的 、表示很宽范围输入信号的能力，从很小的信号到很大的信号。
汇编语言是数字信号处理器使 用的命令语言。为了使常见数字信号处理任务的编程更加方便、
高效，数字信号处理器往往采用专门指令 。例如，多数数字信号处理器都提供多功能指令，这些指

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E
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令利用数字信号处理器的并行结构。数字信号处理器往往还提供高效的循环结构，因为许多数字 信
号处理器运算都包含大量的重复性操作.
为特定应用选择合适的数字信号处理器不 是很容易的。首先要明确的是选择定点器件还是浮点
器件。一般而言，定点器件比较便宜，而且速度也较 快；而浮点器件更便于编程，更适合于运算密
集型的算法。第二，数字信号处理器的数据宽度决定了它所 代表数据的精度。速度也是一个问题，
速度不仅仅是指一秒内有多少个机器周期，而且还包含每个周期能 够执行多少条指令以及这些指令
中的每一条能够完成多少工作。一种评估数字信号处理器最低要求的办法 是：估计对每个到来的样
本必须执行多少条指令。这个数乘以采样频率就得到了所需每秒指令数的最小值 。
某个特定数字信号处理器提供的某些特定的软、硬件特点能够让一种选择优于另一种选择， 可
用片内存储器数量同样也能做到这一点。有的时候，选择数字信号处理器的理由是支撑硬件的匹配性很好，尤其是片上集成的AD和DA转换器。对于低级编程语言和高级编程语言，软件开发工具
是 否高效便捷也是经常要考虑的主要因素；而是否能够得到第三方软件也是主要因素之一。当然了，
成本永 远都是因素之一。事实上，被选中的数字信号处理器往往速度快、功能多，而且也符合资金
预算的要求。
购买数字信号处理器有三种方式：购买内核、购买处理器和购买板级产品。在数字信号处理器中，“内核”这个词是指处理器中运行关键任务的部分；它包括数字寄存器、乘法器、运算逻辑单
元 、地址产生器和程序定序器。一个完整的处理器需要将内核、存储器和外部接口组合起来。尽管
内核设计 和片内外设是分开进行的，但是却被制作在同一片硅片上；这样，处理器就能成为单片集
成电路。
假定你要制造蜂窝电话并希望设计中使用数字信号处理器，你很可能会以处理器的形式购买数< br>字信号处理器；也就是说，你会购买一片内核、存储器和其他内部功能的集成电路。为了在产品中
使用这片集成电路，你必须设计一个印刷电路板，而数字信号处理器将被焊接在这块电路板上，与
其他电 子元件相连。这是使用数字信号处理器最常见的方式。
现在，假设你服务的公司要制造自己的 集成电路。在这种情况下，你可能不会购买整个处理器，
而仅会购买处理器的内核设计。在完成了相应的 授权协议后，你就可以开始制造为特殊用途而定制
的芯片了。这样做给了您选择片内存储器数量、数据收 发方式和封装形式等的自由。在数字信号处
理器市场中，这种定制器件成为越来越重要的一部分。
有几十家公司提供安装了数字信号处理器的印刷电路板。在这些电路板上，有附加存储器、AD
和DA转换器、EPROM插座和多个处理器等。虽然有些电路板可用作独立工作的计算机，但大部分电路板配制成主机（如PC机）插板形式。制造这种电路板的公司被称为“第三方开发商”。寻
找 第三方开发商最好的方法是询问你要使用的数字信号处理器的生产商。查看数字信号处理器生产
商的网站 ；如果在哪里找不到的话，就给生产商发电子邮件。生产商非常乐于告诉你：谁在使用他
们的产品以及如 何与他们联系。
要记住：数字信号处理器和其他微处理器的界限并不是很清晰的。例如，让我 们看一下Intel
是怎样描述奔腾处理器新增的MMX技术的：“为了高效操作和处理视频、音频和图 像数据，Intel
工程师新增了57条功能强大的指令。这些指令面向的是多媒体操作中经常出现的、 高度并行和重复
的程序。”
将来，我们一定会看到更多的数字信号处理器功能融合到 传统的微处理器和微控制器当中。这
种变革的强大推力之一就是网络和其他多媒体应用。这些应用的发展 速度如此之快，以至于20年后
的微处理器很可能也会成为“传统的”微处理器。


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