8:50
Video length is 8:50
Quantization and Precision Loss Diagnostics for Embedded Types
You can model your algorithm in Simulink® using the default double data types for signals and the computations to simulate the ideal numerical behavior. However, when you use embedded data types in your Simulink model, you can encounter certain numerical precision issues because of the quantization error of the chosen data type, either fixed-point or single-precision floating point. Learn how you can leverage various diagnostics and suppression mechanisms to filter out the real precision loss and quantization error issues in your system under design.
Published: 17 Apr 2018
Featured Product
Fixed-Point Designer
Up Next:
Related Videos:
您也可以从以下列表中选择网站:
如何获得最佳网站性能
选择中国网站(中文或英文)以获得最佳网站性能。其他 MathWorks 国家/地区网站并未针对您所在位置的访问进行优化。
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
亚太
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)