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OptimizationResult class

Result after optimizing fixed-point system


An OptimizationResult object contains the results after optimizing a fixed-point system. If the optimization process succeeds in finding a new fixed-point implementation, you can use this object to explore the different implementations that met the specified tolerances found during the process. Use the explore method to open the Simulation Data Inspector and view the behavior of the optimized system.


result = fxpopt(model, sud, options) optimizes the data types in the system specified by sud in the model, model, with additional options specified in the fxpOptimizationOptions object, options.

Input Arguments

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Name of the model containing the system that you want to optimize.

Data Types: char

System whose data types you want to optimize, specified as a character vector containing the path to the system.

Data Types: char

fxpOptimizationOptions object specifying additional options to use during the data type optimization process.


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Message specifying whether the optimization process found a new optimal solution, returned as a character vector.

Data Types: char

The fxpOptimizationOptions object used as an input to the fxpopt function used to generate the OptimizationResult.

A vector of OptimizationSolution objects found during the optimization process. If the optimization finds a feasible solution, the vector is sorted by cost, with the lowest cost (most optimal) solution as the first element of the vector. If the optimization does not find a feasible solution, the vector is sorted by maximum difference from the original design.


exploreExplore fixed-point implementations found during optimization process

Copy Semantics

Handle. To learn how handle classes affect copy operations, see Copying Objects (MATLAB).

Introduced in R2018a