Floating point arithmetic is rarely exact.
浮点运算很少是精确的。
Even under version 7.2, Vim does only floating-point arithmetic if one of the operands is explicitly floating-point.
即使对于版本7.2，如果其中一个运算对象被明确声明为浮点类型，那么Vim只支持浮点算术。
While nearly every processor and programming language supports floating point arithmetic, most programmers pay little attention to it.
虽然几乎每种处理器和编程语言都支持浮点运算，但大多数程序员很少注意它。
It is best to reserve the use of floating point arithmetic for calculations that involve fundamentally inexact values, such as measurements.
最好将浮点运算保留用作计算本来就不精确的数值，譬如测量。
A processor interprets a stream of data as instructions to execute; it has one or more processing units that perform integer and floating-point arithmetic as well as more advanced computations.
处理器将数据流解释为要执行的指令，它拥有一个或多个处理单元，用于执行整数和浮点运算以及更高级的计算。
Fixed-point arithmetic may be employed.
可以采用定点算术。
Real Programmers scorn floating point arithmetic.
真正的程序员鄙视浮点运算。
The floating point arithmetic is very important for high performance arithmetic.
浮点运算是高性能计算研究中的一个重要领域。
Floating point arithmetic is one of the most important one in high performance arithmetic.
浮点运算是高性能计算研究中的一个重要领域。
Block floating-point arithmetic is used to enhance the dynamic range and computation accuracy.
采用块浮点算法以提高动态范围和运算精度。
In this paper we mainly study for the key technology of super precision floating point arithmetic.
本文主要研究超高精度浮点运算中的关键技术。
The 8-neighbour point arithmetic is a simple and effective method to extract the contours in slice image.
采用8邻域轮廓提取算法可以方便地提取到二值化分割后的图像断层轮廓。
Many of the familiar algebraic rules for real number arithmetic do not always hold for floating-point arithmetic.
对于浮点算法而言，许多惯用的实数算法代数规则有时并不适用。
Numerical unstability of FTF algorithm becomes conspicuous especially when the algorithm is implemented by the finite-word-length fixed-point arithmetic.
但是FTF算法具有众所周知的数值性能不稳定性，该问题在用有限字长定点实现时变得尤为明显。
The reason beyond this is that those fast algorithms do reduce the complexity of computing but still one needs to use floating-point arithmetic operations in the computation process.
原因是这些快速算法虽减少了计算复杂性，但在计算过程中仍需要大量浮点运算。
Remember, integer arithmetic is much faster than floating-point arithmetic, as it can usually be done directly by the processor, rather than relying on external FPUs or floating point math libraries.
记住，整形数运算要比浮点数运算快得多，因为处理器可以直接进行整型数运算，浮点数运算需要依赖于外部的浮点数处理器或者浮点数数学库。
This paper describes a 32-bit fixed-point Arithmetic and Logic Unit (ALU).
本文介绍了一种32位定点运算部件的设计方案和实现结果。
This paper describes a 32-bit fixed-point Arithmetic and Logic Unit (ALU).
本文介绍了一种32位定点运算部件的设计方案和实现结果。
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