Floating point is a very similar concept, except that computers use binary rather than decimal as their base.
浮点是一个非常类似的概念，除了计算机使用二进制而不是十进制作为基础。
These are based on the IEEE 754 standard, which defines a binary standard for 32-bit floating point and 64-bit double precision floating point binary-decimal Numbers.
它们都依据IEEE 754标准，该标准为32位浮点和64位双精度浮点二进制小数定义了二进制标准。
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.
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。
Floating binary point types are much faster to work with than decimals.
二进制浮点点类型是更快的工作比小数。
Editing floating-point values can result in minor inaccuracies because of decimal-to-binary conversion of fractional components.
编辑浮点值时，由于要将小数部分从十进制转换为二进制，因此所得的结果可能存在微小误差。
The conversion from binary floating-point representation to decimal representation can be lossy, depending on your conversion Settings.
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。
Binary representation of floating-point values affects the precision and accuracy of floating-point calculations.
二元代表性浮点值影响的精密度和准确度的浮点计算。
Floating-point value are typically stored in computer memory in binary format.
浮点值通常是在二进制格式存储在计算机内存中。
Floating-point decimal values generally do not have an exact binary representation.
一般而言，十进位浮点数值并没有精确的二进位表示式。
Floating-point decimal values generally do not have an exact binary representation.
一般而言，十进位浮点数值并没有精确的二进位表示式。
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