这就是所谓的浮点表示法。
数据采用块浮点表示，提高了运算精度。
Using block-floating point arithmetic, the processor can provide a high quality.
这是一个标准的浮点表示法，特点是尾数的第一个元不可以是零。
This is a standard floating point representation that the first bit of mantissa must be 1.
二进制浮点表示的转换十进制表示可以损耗，根据您的转换设置。
The conversion from binary floating-point representation to decimal representation can be lossy, depending on your conversion Settings.
还可以使用指数表示浮点数，参见清单8。
Floats can also be expressed using exponents, as shown Listing 8.
浮点或者双精度浮点的内存空间是限定了的，所以某些值不能被表示。
The memory space of a float or double value is limited, so some values cannot be represented.
该方法的参数包括：一个整数，指示更改的传感器；一个浮点值数组，表示传感器数据本身。
The arguments to the method include an integer that identifies the sensor that changed, along with an array of float values representing the sensor data itself.
域是类或类型并表示数据的规则、语法及语义(例如，它必需是整型、浮点型、图片类型等等)。
A domain is a class or type and indicates the rules, syntax, and semantics for a piece of data (for example, it must be an integer, float, conform to a picture, and so on).
HTTP内容协商使用短浮点数来表示各种可协商参数的相对重要性（或权重）。
HTTP content negotiation uses short floating point numbers to indicate the relative importance, or weight, of various negotiable parameters.
IEEE 754用科学记数法以底数为2的小数来表示浮点数。
IEEE 754 represents floating point Numbers as base 2 decimal Numbers in scientific notation.
在大部分的编程语言中，包含了小数点的数字称之为浮点数，可以用它来表示数学中的实数。
In most programming languages, Numbers that include a decimal fraction are called floating-point Numbers, which are used to approximate real Numbers in mathematics.
浮点数最好用来表示象测量值这类数值，这类值从一开始就不怎么精确。
Floating point Numbers are best reserved for values such as measurements, whose values are fundamentally inexact to begin with.
它只是返回一个表示温度的浮点数。
All it does is return a floating point number representing the temperature.
根据IEEE浮点标准，它只是值的文本表示。
It is simply a textual representation of the value according to the IEEE floating point standard.
其中一个构造函数以双精度浮点数作为输入，另一个以整数和换算因子作为输入，还有一个以小数的String表示作为输入。
One takes a double-precision floating point as input, another takes an integer and a scale factor, and another takes a String representation of a decimal number.
不要用浮点值表示精确值。
比如0.1不能被表示为二进制数，所以被四舍五入储存为双精度浮点数。
For example, 0.1 cannot be represented binary, and therefore is rounded when stored in a double. Let me show you using python.
Derby对实数提供了多种格式的支持：单精度浮点、双精度浮点以及准确的算术表示，如表2所示。
Derby provides support for real Numbers in several formats: single-precision floating-point, double-precision floating-point, and an exact representation decimal, as presented in Table 2.
综合起来，浮点数是这样表示的：sign*mantissa*2exponent 。
Putting these together, a float is interpreted as sign * mantissa * 2exponent.
浮点数和双精度数字的二进制表示。
您可以将输出显示为八进制、十六进制、十进制、浮点数、包含反斜杠转义符的ASCII，或者指定的字符(nl表示换行、ht表示水平制表符，等等)。
You can display output as octal, hex, decimal, floating point, ASCII with backslash escapes, or named characters (nl for newline, ht for horizontal TAB, etc.).
因为在内部，计算机使用一种非精确的(二进制浮点数)形式表示诸如0.1,0.2,0.3之类的小数。
Because internally, computers use a format (binary floating-point) that cannot accurately represent a number like 0.1, 0.2 or 0.3 at all.
浮点数表示法，含部份换轴之高斯消去法，使用矩阵大小之计算尺度调整，带状及三角对角系统，LU分解。
Floating point representation, Gaussian elimination with partial pivoting, scaling of computations with matrix size, banded and tri-diagonal systems, LU decomposition.
另外，为了避免溢出，还采用块浮点结构表示数据，节省了大量的硬件资源。
Moreover, in order to avoid overflowing, it also USES block-floating-piont structure that can save many hardware resources.
将指定之数字的字串表示，转换为相等的双精确度浮点数。
Converts the specified string representation of a number to an equivalent double-precision floating-point number.
传统的以浮点矢量形式表示的图像特征，是基于内容的图像检索技术的基础。
The traditional float vector based image feature is the base of content based image retrieval techniques.
一个表示触摸板触摸位置的转动位置的浮点数，0是顶部，180是底部，其他角度随之对应。
A float that shows the rotational position the touchpad is being touched at, 0 being top, 180 being bottom and all other angles accordingly.
在此实例的结尾追加指定的单精度浮点数的字符串表示形式。
Appends the string representation of a specified subarray of Unicode characters to the end of this instance.
当浮点数从一种表示形式转换为另一种表示形式时，该数字的最低有效位数可能稍有变化。
When a floating point number is converted from one representation to another representation, the least significant digits of that number may vary slightly.
当浮点数从一种表示形式转换为另一种表示形式时，该数字的最低有效位数可能稍有变化。
When a floating point number is converted from one representation to another representation, the least significant digits of that number may vary slightly.
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