Lookup-Tabellen-Optimierung
R2026bLookup-Tabellen sind eine effiziente Methode, rechnerisch aufwändige Funktionen für Embedded-Geräte mit Festkomma zu schreiben. Beispielsweise können Sie mithilfe von Lookup-Tabellen effizient Logarithmus, Sinus und Quadratwurzel implementieren. Mithilfe der Lookup Table Optimizer-App können Sie speichereffiziente Lookup-Tabellen generieren, mit denen sich Funktionen, Subsysteme und Blöcke approximieren lassen. Sie können sie zudem zur Optimierung einer bestehenden Lookup-Tabelle und dadurch zur Reduzierung der Speichernutzung verwenden.
Apps
| Lookup Table Optimizer | Optimize existing lookup table or approximate function with lookup table |
Klassen
FunctionApproximation.Problem | Object defining the function to approximate, or the lookup table to optimize |
FunctionApproximation.Options | Specify additional options to use with
FunctionApproximation.Problem object |
FunctionApproximation.LUTSolution | Optimized lookup table data or lookup table data approximating a math function |
FunctionApproximation.LUTMemoryUsageCalculator | Calculate memory used by lookup table blocks in a system |
FunctionApproximation.TransformFunction | Object defining transform function to approximate (Seit R2023a) |
Objekte
LUTCompressionResult | Optimized lookup table data for all Lookup Table blocks in a system |
Funktionen
Themen
Lookup Table Optimizer-App-Workflow
- Optimize Lookup Tables for Memory-Efficiency
Optimize Lookup Tables using the Lookup Table Optimizer. - Generate an Optimized Lookup Table as a MATLAB Function
Use the Lookup Table Optimizer to generate a lookup table as a MATLAB® function.
Befehlszeilen-Workflow für den Lookup Table Optimizer
- Optimize Lookup Tables for Memory-Efficiency Programmatically
Optimize an existing lookup table, generate a lookup table from a Math Function block or function handle. - Optimize Lookup Tables for Multiple Functions
Speed up lookup table optimization by sharing breakpoints and prelookup tasks between multiple functions. (Seit R2026b) - Fixed-Point Function Approximation
When a fixed-point library function is not available, fixed-point applications require an approximation of the function. - Approximate Functions with a Direct Lookup Table
Generate direct lookup table approximations of functions or blocks. - Replace Fitted Curve with Optimized Lookup Table
Reduce the size of lookup tables for functions with symmetry. - Generate an Optimized Lookup Table as a MATLAB Function Programmatically
Programmatically generate an optimized lookup table as a MATLAB function. - Optimize Lookup Tables for Periodic Functions
Reduce the size of lookup tables for functions with symmetry.
Prelookup und Interpolation in Simulink
- Fixed-Point Prelookup and Interpolation
This example demonstrates some of the features of Prelookup and Interpolation Using Prelookup blocks. - Sharing Parameters in Prelookup and Interpolation Blocks
This example shows how Prelookup and Interpolation blocks share their parameter data in generated code. - High Precision Calculations in Interpolation Block
This example shows how to perform high precision calculations in the Interpolation Using Prelookup block using internal rules. - Shared Utility Functions for Prelookup Blocks
This example shows how Prelookup blocks share utility functions.
Implementieren von Lookup-Tabellen in MATLAB
- Normalize Data for Lookup Tables
This example shows how to normalize data for use in lookup tables. - Implement Fixed-Point Log2 Using Lookup Table
This example shows how to implement fixed-point log2 using a lookup table. Lookup tables generate efficient code for embedded devices. - Implement Fixed-Point Square Root Using Lookup Table
This example shows how to implement fixed-point square root using a lookup table.
Enthaltene Beispiele
Calculate Complex dB Using a Direct Lookup Table
Create an optimized direct lookup table calculating decibel levels.
Image Denoising Using Fixed-Point Quantized Restricted Boltzmann Machine Algorithm
Convert a Restricted Boltzmann Machine (RBM) algorithm to an embedded-efficient version.
Reduce Memory Footprint Using Shared Lookup Tables
Find Simulink® lookup table blocks with shared inputs, optimize them to share one set of breakpoint vectors, and validate the lookup table approximation using the downstream outputs of the model. Sharing breakpoints can speed up optimization and reduce total memory footprint. The example uses an interior permanent magnet synchronous motor (IPMSM) controller. You use a variant subsystem to implement the optimized lookup tables and compare their memory footprint and behavior to the originals.
