Limitations on precision, effects of rounding and padding

Examples and How To

Maximize Precision

Precision is limited by slope. To achieve maximum precision, you should make the slope as small as possible while keeping the range adequately large.

Limitations on Precision and Errors

Fixed-point variables have a limited precision because digital systems represent numbers with a finite number of bits.

Pad with Trailing Zeros

Padding with trailing zeros involves extending the least significant bit (LSB) of a number with extra bits. This method involves going from low precision to higher precision.

Detect Net Slope and Bias Precision Issues

Receive alerts when fixed-point constant precision issues occur.

Detect Fixed-Point Constant Precision Loss

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


Fixed-Point Arithmetic Operations

Provides an overview of issues that need to be considered when performing fixed-point arithmetic operations—overflow, quantization, computational noise, and limit cycles

Limitations on Precision

Computer words consist of a finite numbers of bits. This means that the binary encoding of variables is only an approximation of an arbitrarily precise real-world value.

Rules for Arithmetic Operations

Describes the rules that the Simulink® software follows when arithmetic operations are performed on inputs and parameters.

Net Slope and Net Bias Precision

Represent a fixed-point number by a general slope and bias encoding scheme.


Rounding involves going from high precision to lower precision and produces quantization errors and computational noise.

Rounding Modes for Fixed-Point Simulink Blocks

Fixed-point Simulink blocks support seven different rounding modes.

Was this topic helpful?