|
Abstract
|
|
|---|---|
| Systems based on fixed-point arithmetic, when carefully designed, seem to behave as their infinite precision analogues. Most often, however, this is only a macroscopic impression: finite word-lengths inevitably approximate the reference behavior introducing quantization errors, and confine the macroscopic correspondence to a restricted range of input values. Understanding these differences is crucial to design optimized fixed-point implementations that will behave ?as expected? upon deployment. Thus, in this chapter, we survey the main approaches proposed in literature to model the impact of finite precision in fixed-point systems. In particular, we focus on the rounding errors introduced after reducing the number of least-significant bits in signals and coefficients during the so-called quantization process. | |
|
International
|
Si |
|
|
10.1007/978-3-319-91734-4_29 |
|
Book Edition
|
|
|
Book Publishing
|
|
|
ISBN
|
978-3-319-91733-7 |
|
Series
|
|
|
Book title
|
Handbook of Signal Processing Systems |
|
From page
|
1063 |
|
To page
|
1101 |