Floating Point Representation (CHAPTER 01.05)
Floating Point Representation of Numbers
Summary
This video shows that before delving into floating point representation in binary format, we would be better off by revisiting fixed (decimal) format and floating point (scientific) format for base-10 numbers. The limits on the range of numbers representable, true errors, and relative true errors is looked at. This will ease the student into the floating point representation of binary numbers.
Learning Objective
After watching this video, revisit floating-point representation for base-10 numbers, define mantissa, exponent, and base of a floating point number, find the range of numbers that can be represented, and identify that absolute true errors in representing numbers are bounded for the fixed format, while absolute relative true errors in representing numbers are bounded for floating point format.
Transcript
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Annotated Slides
All Videos for this Topic
Floating Point Representation Background: Part 1 of 3 [YOUTUBE 7:37]
Floating Point Representation Background: Part 2 of 3 [YOUTUBE 10:43]
Floating Point Representation Background: Part 3 of 3[ YOUTUBE 1:58]
Floating Point Representation: Example: [YOUTUBE 7:50]
Floating Point Representation – Biased Exponent: Example[YOUTUBE 8:51]
IEEE-754 Single Precision Representation: Part 1 of 2 [YOUTUBE 4:57]
IEEE-754 Single Precision Representation: Part 2 of 2 [YOUTUBE 8:38]
Complete Resources
Get in one place the following: Floating Point Representation