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Overflow and Precision Loss Detection

Debug sources of overflow and precision loss, compare to floating-point behavior

Identify, trace, and debug sources of overflow, precision loss, and wasted range or precision. Compare embedded implementation against ideal floating-point behavior.

Topics

MATLAB

Data Type Override Preferences Using fipref

Data type override using the fipref object.

Underflow and Overflow Logging Using fipref

Examples of using fipref objects to set logging preferences for fi objects.

Compute Quantization Error

This example shows how to compute and compare the statistics of the signal quantization error when using various rounding methods.

Visualize Differences Between Floating-Point and Fixed-Point Results

Use a custom plot function to compare the behavior of the generated fixed-point code against the behavior of the original floating-point MATLAB code.

Enable Plotting Using the Simulation Data Inspector

Inspect and compare floating-point and fixed-point logged input and output data.

Custom Plot Functions

Visualize numerical differences during fixed-point conversion.

Detect Overflows

Detect overflows using the app.

Simulink

Use the Fixed-Point Tool to Explore Numerical Behavior

Example showing how to use the Fixed-Point Tool to compare floating-point and fixed-point data types.

Handle Overflows in Simulink Models

Control the warning messages you receive when a model contains an overflow.

Net Slope and Net Bias Precision

Net slope and bias precision, detecting precision loss, underflow, and overflow.

Detect Fixed-Point Constant Precision Loss

This example shows how to detect fixed-point constant precision loss.

Use Scaled Doubles to Avoid Precision Loss

How to avoid precision loss by overriding the data types in your model with scaled doubles.