Schätzen von Funktionen mit Lookup-Tabellen
Mit Lookup Table Optimizer können Sie speichereffiziente Lookup-Tabellen generieren, mit denen sich Funktionen, Subsysteme und Blöcke schätzen lassen. Sie können sie zudem verwenden, um einen bestehenden Lookup Table-Block zu optimieren.
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
FunctionApproximation.compressLookupTables | Compress all Lookup Table blocks in a system |
coder.approximation | Create function replacement configuration object |
DataTypeWorkflow.findDecoupledSubsystems | Get a list of subsystems to replace with an approximation |
Themen
- Optimize Lookup Tables for Memory-Efficiency
Optimize Lookup Tables using the 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.
- Generate an Optimized Lookup Table as a MATLAB Function
Use the Lookup Table Optimizer to generate a lookup table as a MATLAB® function.
- Generate an Optimized Lookup Table as a MATLAB Function Programmatically
Programmatically generate an optimized lookup table as a MATLAB function.
- Approximate Functions with a Direct Lookup Table
Generate direct lookup table approximations of functions or blocks.
- Convert Floating-Point Model to Fixed Point
Use the Fixed-Point Tool to convert a floating-point model to fixed point.
Enthaltene Beispiele
Fixed-Point Function Approximation
When a fixed-point library function is not available, fixed-point applications require an approximation of the function. Often, an interpolated look up table is used to store an approximation of the function over a specified range.
Calculate Complex dB Using a Direct Lookup Table
Create an optimized direct lookup table calculating decibel levels.
Convert Neural Network Algorithms to Fixed-Point Using fxpopt and Generate HDL Code
Convert a neural network to fixed point using fixed-point optimization and lookup table optimization.
Convert Neural Network Algorithms to Fixed Point and Generate C Code
Convert a neural network to fixed point using the Fixed-Point Tool and lookup table optimization.
Convert Digit Recognition Neural Network to Fixed Point and Generate C Code
Create an embedded efficient neural network using the Fixed-Point Tool and Lookup Table Optimizer.
Image Denoising Using Fixed-Point Quantized Restricted Boltzmann Machine Algorithm
Convert a Restricted Boltzmann Machine (RBM) algorithm to an embedded-efficient version.
Optimize Lookup Tables for Periodic Functions
Reduce the size of lookup tables for functions with symmetry.
Replace Fitted Curve with Optimized Lookup Table
Reduce the size of lookup tables for functions with symmetry.
High Precision Calculations in Interpolation Block
Perform high precision calculations in the Interpolation Using Prelookup block using internal rules. The Interpolation block allows the data type for intermediate results to be set.
Fixed-Point Prelookup and Interpolation
Demonstrates some of the features of Prelookup and Interpolation Using Prelookup blocks.
Sharing Parameters in Prelookup and Interpolation Blocks
How Prelookup and Interpolation blocks share their parameter data in generated code.
Shared Utility Functions for Prelookup Blocks
How Prelookup blocks share utility functions. The utility functions generated by the Prelookup block are determined by the target data type of the block's inputs, outputs, and breakpoint parameter, as well as the Index search method and Integer rounding mode. Even if the two Prelookup blocks in this model have different data types, they fulfill the above requirements and share their utility functions.
