Lecture
Floating Point Numbers: Extended Precision
Description
This lecture covers the representation of numbers using extended floating point notation, focusing on the smallest representable number and the convention changes to represent numbers smaller than 1. The instructor explains how to interpret the exponent 0 differently, shifting the exponent range to include negative powers. By adjusting the representation convention, the interval between 0 and 2 is used to represent values smaller than 1, resulting in a loss of precision. An example with a specific exponent value is provided to illustrate the representation process. The lecture concludes with a simple representation of 0 using all zeros.
Instructor
voluptate cupidatat
Do id aute laborum amet enim consequat labore aliquip nisi occaecat sint minim incididunt occaecat. Excepteur dolor exercitation consectetur adipisicing. Veniam ad ut nulla ad cillum fugiat laborum consequat veniam in. Culpa velit exercitation aliquip amet labore aliquip ut. Deserunt enim nulla eiusmod velit ullamco et irure commodo voluptate non aliqua. Eu adipisicing sint anim consequat eu ea sunt quis.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (25)
Computer Arithmetic: Floating Point Operations
Covers the basics of computer arithmetic, focusing on floating point numbers and their operations.
Computer Arithmetic: Floating Point Numbers
Explores computer arithmetic, emphasizing fixed-point and floating-point numbers, IEEE 754 standard, dynamic range, and floating-point operations in MIPS architecture.
Numerical Analysis: Algorithms and Concepts
Covers algorithms for mathematical problems, focusing on stability, precision, and critical result analysis.
Information Representation: Binary Representations
Explores binary information representation, efficiency, byte usage, and integer representation.
Floating Point Representation: Consequences for Programming
Explores the consequences of floating-point representation errors in programming, emphasizing precision and computational costs.