Data Type Propagation

Set data type and scaling of propagated signal based on information from reference signals

Libraries:
Simulink / Signal Attributes
HDL Coder / Signal Attributes

Description

The Data Type Propagation block allows you to control the data type and scaling of signals in your model. You can use this block along with fixed-point blocks that have their Output data type parameter configured to Inherit: Inherit via back propagation.

The block has three inputs: Ref1 and Ref2 are the reference inputs, while the Prop input back-propagates the data type and scaling information gathered from the reference inputs. This information is then passed on to other fixed-point blocks.

The block provides many choices for propagating data type and scaling information. For example, you can use:

The number of bits from the Ref1 reference signal or the number of bits from widest reference signal
The range from the Ref2 reference signal or the range of the reference signal with the greatest range
A bias of zero, regardless of the biases used by the reference signals
The precision of the reference signal with the least precision

You specify how data type information is propagated using the Propagated data type parameter:

If you select Specify via dialog, then you manually specify the data type via the Propagated data type edit field.
If you select Inherit via propagation rule, then you must use the parameters described in Parameters.

You specify how scaling information is propagated using the Propagated scaling parameter:

If you select Specify via dialog, then you manually specify the scaling via the Propagated scaling edit field.
If you select Inherit via propagation rule, then you must use the parameters described in Parameters.

After you use the information from the reference signals, you can apply a second level of adjustments to the data type and scaling. To do so, use individual multiplicative and additive adjustments. This flexibility has various uses. For example, if you are targeting a DSP, then you can configure the block so that the number of bits associated with a multiply and accumulate (MAC) operation is twice as wide as the input signal, and has a specific number of guard bits added to it.

The Data Type Propagation block also provides a mechanism to force the computed number of bits to a useful value. For example, if you are targeting a 16-bit micro, then the target C compiler is likely to support sizes of only 8 bits, 16 bits, and 32 bits. The block forces these three choices to be used. For example, suppose that the block computes a data type size of 24 bits. Since 24 bits is not directly usable by the target chip, the signal is forced up to 32 bits, which is natively supported.

There is also a method for dealing with floating-point reference signals. This method makes it easier to create designs that are easily retargeted between fixed-point chips and floating-point chips.

The Data Type Propagation block allows you to set up libraries of useful subsystems that are properly configured based on the connected signals. Without this data type propagation process, subsystems from a library are unlikely to work as desired with most integer or fixed-point signals. Manual intervention would be required to configure the data type and scaling. In many situations, this block can eliminate the manual intervention.

Precedence Rules

The precedence of the dialog box parameters decreases from top to bottom. Also:

Double-precision reference inputs have precedence over all other data types.
Single-precision reference inputs have precedence over integer and fixed-point data types.
Multiplicative adjustments are carried out before additive adjustments.
The number of bits is determined before the precision or positive range is inherited from the reference inputs.
PosRange is one bit higher than the exact maximum positive range of the signal.
The computed number-of-bits are promoted to the smallest allowable value that is greater than or equal to the computation. If none exists, then the block returns an error.

Examples

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Propagate Data Types in a Simulink Model

Open Script

This example shows how to propagate data types in a Simulink model, using a Data Type Propagation block.

This model adds two numbers of datatypes int8 and int64. The blocks in the model use the following parameters:

In the block parameters for the Inport blocks, under the Signal Attributes tab, the first Inport's Data type is int8 and the second Inport's Data type is int64.
In the block parameters of the Add block, the Output data type is Inherit: Inherit via back propagation. This allows the Data Type Propagation block to define the output data type of the block.
In the block parameters of the Data Type Propagation block, in the Propagated type tab, Propagated data type is Inherit via propagation rule.
The data types of the inports are displayed by selecting Debug > Diagnostics > Information Overlays > PORTS > Base Data Types. This is used to show how the sum's data type changes under different parameters.

open_system('DataTypePropagation')

To observe how the Data Type Propagation block impacts the data type of the sum, modify the Block Parameters:

In the Block Parameters of the Data Type Propagation block, Number-of-Bits is set to max([NumBits1 NumBits2]). Press Ctrl-D to compile and update the model. Observe that the data type of the output is now int64, the max bits out of 8 bits and 64 bits.

In the Block Parameters of the Data Type Propagation block, Number-of-Bits is set to NumBits1+NumBits2. Update the diagram again. Observe that the size of the output data type is now 72 bits, which is the sum of the input integer lengths.

In the Block Parameters of the Data Type Propagation block, Is-Signed is set to FALSE. Update the diagram again. Observe that the data type of the output is now ufix72, an unsigned 72 bit integer.

Ports

Input

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Ref1 — First reference signal
scalar | vector | matrix | N-D array

First reference signal, from which to gather data type and scaling information.

Ref2 — Second reference signal
scalar | vector | matrix | N-D array

Second reference signal from which to gather data type and scaling information.

Prop — Propagated data type and scaling
data type and scaling

Data type and scaling information, back-propagated to the model. After the block gathers data type and scaling information from the reference signals, you can apply a second level of adjustments to the data type and scaling. To do so, specify individual multiplicative and additive adjustments in the block dialog box.

Parameters

expand all

Propagated Type

1. Propagated data type — Mode of specifying propagated data type
`Inherit via propagation rule` (default) | `Specify via dialog`

Specify whether to propagate the data type via the dialog box, or inherit the data type from the reference signals.

Programmatic Use

Block Parameter: PropDataTypeMode

Type: character vector

Values:

'Specify via dialog' | 'Inherit via propagation
										rule'

Default: 'Inherit via propagation rule'

1.1. Propagated data type (e.g. fixdt(1,16), fixdt('single')) — Propagated data type
`fixdt(1,16)` (default) | data type string

Specify the data type to propagate.

Dependencies

To enable this parameter, set 1. Propagated data type to Specify via dialog.

Programmatic Use

Block Parameter: PropDataType

Type: character vector

Values: 'fixdt(1, 16)' | data type string in quotes

Default: 'fixdt(1, 16)'

1.1 If any reference input is double, output is — Output data type when a reference input is double
`double` (default) | `single`

Specify the output data type as single or double. This parameter makes it easier to create designs that are easily retargeted between fixed-point chips and floating-point chips.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: IfRefDouble

Type: character vector

Values: 'double' | 'single'

Default: 'double'

1.2 If any reference input is single, output is — Output data type when a reference input is single
`single` (default) | `double`

Specify the output data type as single or double. This parameter makes it easier to create designs that are easily retargeted between fixed-point chips and floating-point chips.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: IfRefSingle

Type: character vector

Values: 'double' | 'single'

Default: 'single'

1.3 Is-Signed — Signedness of propagated data type
`IsSigned1 or IsSigned2` (default) | `IsSigned1` | `IsSigned2` | `TRUE` | `FALSE`

Specify the sign of Prop as one of the following values.

Parameter Value	Description
`IsSigned1`	Prop is a signed data type if Ref1 is a signed data type.
`IsSigned2`	Prop is a signed data type if Ref2 is a signed data type.
`IsSigned1 or IsSigned2`	Prop is a signed data type if either Ref1 or Ref2 are signed data types.
`TRUE`	Ref1 and Ref2 are ignored, and Prop is always a signed data type.
`FALSE`	Ref1 and Ref2 are ignored, and Prop is always an unsigned data type.

For example, if the Ref1 signal is ufix(16), the Ref2 signal is sfix(16), and the Is-Signed parameter is IsSigned1 or IsSigned2, then Prop is forced to be a signed data type.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: IsSigned

Type: character vector

Values:

'IsSigned1' | 'IsSigned2' | 'IsSigned1 or IsSigned2' |
										'TRUE' | 'FALSE'

Default: 'IsSigned1 or IsSigned2'

1.4.1 Number-of-bits: Base — Number of bits for the base of the propagated data type
`max([NumBits1 NumBits2])` (default) | `NumBits1` | `NumBits2` | `min([NumBits1 NumBits2])` | `NumBits1+NumBits2`

Specify the number of bits used by Prop for the base data type as one of the following values.

Parameter Value	Description
`NumBits1`	The number of bits for Prop is given by the number of bits for Ref1.
`NumBits2`	The number of bits for Prop is given by the number of bits for Ref2.
`max([NumBits1 NumBits2])`	The number of bits for Prop is given by the reference signal with largest number of bits.
`min([NumBits1 NumBits2])`	The number of bits for Prop is given by the reference signal with smallest number of bits.
`NumBits1+NumBits2`	The number of bits for Prop is given by the sum of the reference signal bits.

For more information about the base data type, refer to Targeting an Embedded Processor (Fixed-Point Designer).

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: NumBitsBase

Type: character vector

Values:

'NumBits1' | 'NumBits2' | 'max([NumBits1 NumBits2])' |
										'min([NumBits1 NumBits2])' |
									'NumBits1+NumBits2'

Default: 'max([NumBits1 NumBits2])'

1.4.2 Number-of-bits: Multiplicative adjustment — Number of bits for multiplicative adjustment of propagated data type
`1` (default) | positive integer

Specify the number of bits used by Prop by including a multiplicative adjustment that uses a data type of double. For example, suppose that you want to guarantee that the number of bits associated with a multiply and accumulate (MAC) operation is twice as wide as the input signal. To do this, set this parameter to 2.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: NumBitsMult

Type: character vector

Values: positive integer

Default: '1'

1.4.3 Number-of-bits: Additive adjustment — Number of bits for additive adjustment of propagated data type
`0` (default) | positive integer

Specify the number of bits used by Prop by including an additive adjustment that uses a data type of double. For example, if you are performing multiple additions during a MAC operation, the result could overflow. To prevent overflow, you can associate guard bits with the propagated data type. To associate four guard bits, you specify the value 4.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: NumBitsAdd

Type: character vector

Values: scalar

Default: '0'

1.4.4 Number-of-bits: Allowable final values — Allowable number of bits in propagated data type
`'-1'` (default) | scalar or vector of positive integers

Force the computed number of bits used by Prop to a useful value. For example, if you are targeting a processor that supports only 8 bits, 16 bits, and 32 bits, then you configure this parameter to [8,16,32]. The block always propagates the smallest specified value that fits. If you want to allow all fixed-point data types, you would specify the value -1.

Dependencies

To enable this parameter, set Propagated data type to Inherit via propagation rule.

Programmatic Use

Block Parameter: NumBitsAllowFinal

Type: character vector

Values: scalar or vector of positive integers

Default: '-1'

Propagated Scaling

2. Propagated scaling — Propagated scaling mode
`Inherit via propagation rule` (default) | `Specify via dialog` | `Obtain via best precision`

Choose to propagate the scaling via the dialog box, inherit the scaling from the reference signals, or calculate the scaling to obtain best precision.

Programmatic Use

Block Parameter: PropScalingMode

Type: character vector

Values: 'Inherit via propagation rule' | 'Specify via dialog' |

'Obtain
										via best precision'

Default: 'Inherit via propagation rule'

2.1. Propagated scaling (Slope, e.g. 2^-9 or [Slope Bias], e.g. [1.25 3]) — Slope or slope and bias
`2^-10` | slope | slope and bias in square brackets

Specify the scaling as either a slope or a slope and bias.

Dependencies

To enable this parameter, set Propagated scaling to Specify via dialog.

Programmatic Use

Block Parameter: PropScaling

Type: character vector

Values: slope | slope and bias in square brackets

Default: '2^-10'

2.1. Values used to determine best precision scaling — Values to constrain precision
`[5 -7]` (default)

Specify any values to be used to constrain the precision, such as the upper and lower limits on the propagated input. Based on the data type, the block selects a scaling such that these values can be represented with no overflow error and minimum quantization error.

Dependencies

To enable this parameter, set Propagated scaling to Obtain via best precision.

Programmatic Use

Block Parameter: ValuesUsedBestPrec

Type: character vector

Values: vector of values

Default: '[5 -7]'

2.1.1. Slope: Base — Slope for base of the propagated data type
`min([Slope1 Slope2])` (default) | `Slope1` | `Slope2` | `min([Slope1 Slope2])` | `max([Bias1 Bias2])` | `Slope1Slope2` | `Slope1/Slope2` | `PosRange1` | `PosRange2` | `max([PosRange1 PosRange2])` | `min([PosRange1 PosRange2])` | `PosRange1PosRange2` | `PosRange1/PosRange2`

Specify the slope used by Prop for the base data type as one of the following values.

Parameter Value	Description
`Slope1`	The slope of Prop is given by the slope of Ref1.
`Slope2`	The slope of Prop is given by the slope of Ref2.
`max([Slope1 Slope2])`	The slope of Prop is given by the maximum slope of the reference signals.
`min([Slope1 Slope2])`	The slope of Prop is given by the minimum slope of the reference signals.
`Slope1*Slope2`	The slope of Prop is given by the product of the reference signal slopes.
`Slope1/Slope2`	The slope of Prop is given by the ratio of the Ref1 slope to the Ref2 slope.
`PosRange1`	The range of Prop is given by the range of Ref1.
`PosRange2`	The range of Prop is given by the range of Ref2.
`max([PosRange1 PosRange2])`	The range of Prop is given by the maximum range of the reference signals.
`min([PosRange1 PosRange2])`	The range of Prop is given by the minimum range of the reference signals.
`PosRange1*PosRange2`	The range of Prop is given by the product of the reference signal ranges.
`PosRange1/PosRange2`	The range of Prop is given by the ratio of the Ref1 range to the Ref2 range.

You control the precision of Prop with Slope1 and Slope2, and you control the range of Prop with PosRange1 and PosRange2. Also, PosRange1 and PosRange2 are one bit higher than the maximum positive range of the associated reference signal.

Dependencies

To enable this parameter, set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: SlopeBase

Type: character vector

Values:

'Slope1' | 'Slope2' | 'max([Slope1 Slope2])' |
										'min([Slope1 Slope2])' | 'Slope1*Slope2' | 'Slope1/Slope2' |
										'PosRange1' | 'PosRange2' | 'max([PosRange1 PosRange2])' |
										'min([PosRange1 PosRange2])' | 'PosRange1*PosRange2' |
										'PosRange1/PosRange2'

Default: 'min([Slope1 Slope2])'

2.1.2. Slope: Multiplicative adjustment — Slope of multiplicative adjustment of propagated data type
`1` (default) | scalar

Specify the slope used by Prop by including a multiplicative adjustment that uses a data type of double. For example, if you want 3 bits of additional precision (with a corresponding decrease in range), the multiplicative adjustment is 2^-3.

Dependencies

To enable this parameter, set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: SlopeMult

Type: character vector

Values: scalar

Default: '1'

2.1.3. Slope: Additive adjustment — Slope of additive adjustment of propagated data type
`0` (default) | scalar

Specify the slope used by Prop by including an additive adjustment that uses a data type of double. An additive slope adjustment is often not needed. The most likely use is to set the multiplicative adjustment to 0, and set the additive adjustment to force the final slope to a specified value.

Dependencies

To enable this parameter, set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: SlopeAdd

Type: character vector

Values: scalar

Default: '0'

2.2.1. Bias: Base — Base bias for Prop
`Bias1` (default) | `Bias2` | `max([Bias1 Bias2])` | `min([Bias1 Bias2])` | `Bias1*Bias2` | `Bias1/Bias2` | `Bias1+Bias2` | `Bias1-Bias2`

Specify the bias used by Prop for the base data type. The parameter values are described as follows:

Parameter Value	Description
`Bias1`	The bias of Prop is given by the bias of Ref1.
`Bias2`	The bias of Prop is given by the bias of Ref2.
`max([Bias1 Bias2])`	The bias of Prop is given by the maximum bias of the reference signals.
`min([Bias1 Bias2])`	The bias of Prop is given by the minimum bias of the reference signals.
`Bias1*Bias2`	The bias of Prop is given by the product of the reference signal biases.
`Bias1/Bias2`	The bias of Prop is given by the ratio of the Ref1 bias to the Ref2 bias.
`Bias1+Bias2`	The bias of Prop is given by the sum of the reference biases.
`Bias1-Bias2`	The bias of Prop is given by the difference of the reference biases.

Dependencies

To enable this parameter, set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: BiasBase

Type: character vector

Values:

'Bias1' | 'Bias2' | 'max([Bias1 Bias2])' | 'min([Bias1
										Bias2])' | 'Bias1*Bias2' | 'Bias1/Bias2' | 'Bias1+Bias2' |
										'Bias1-Bias2'

Default: 'Bias1'

2.2.2. Bias: Multiplicative adjustment — Multiplicative bias for propagated data type
`1` (default) | scalar

Specify the bias used by Prop by including a multiplicative adjustment that uses a data type of double.

This parameter is visible only when you set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: BiasMult

Type: character vector

Values: scalar

Default: '1'

2.3.2. Bias: Additive adjustment — Additive bias for propagated data type
`0` (default) | scalar

Specify the bias used by Prop by including an additive adjustment that uses a data type of double.

If you want to guarantee that the bias associated with Prop is zero, configure both the multiplicative adjustment and the additive adjustment to 0.

Dependencies

To enable this parameter, set Propagated scaling to Inherit via propagation rule.

Programmatic Use

Block Parameter: BiasAdd

Type: character vector

Values: scalar

Default: '0'

Block Characteristics

Data Types	`Boolean` \| `double` \| `fixed point` \| `half` \| `integer` \| `single`
Direct Feedthrough	`no`
Multidimensional Signals	`yes`
Variable-Size Signals	`yes`
Zero-Crossing Detection	`no`

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

HDL Coder™ provides additional configuration options that affect HDL implementation and synthesized logic.

HDL Architecture

This block can be used to control scaling and data types of signals that are part of subsystems that generate HDL code, but is not included in the hardware implementation.

Limitations

When this block is present inside the masked subsystem, the block is ignored in model generation.

Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.

Version History

Introduced before R2006a

Data Type Propagation

Description

Precedence Rules

Examples

Propagate Data Types in a Simulink Model

Ports

Input

Ref1 — First reference signal scalar | vector | matrix | N-D array

Ref2 — Second reference signal scalar | vector | matrix | N-D array

Prop — Propagated data type and scaling data type and scaling

Parameters

Propagated Type

1. Propagated data type — Mode of specifying propagated data type Inherit via propagation rule (default) | Specify via dialog

Programmatic Use

1.1. Propagated data type (e.g. fixdt(1,16), fixdt('single')) — Propagated data type fixdt(1,16) (default) | data type string

Dependencies

Programmatic Use

1.1 If any reference input is double, output is — Output data type when a reference input is double double (default) | single

Dependencies

Programmatic Use

1.2 If any reference input is single, output is — Output data type when a reference input is single single (default) | double

Dependencies

Programmatic Use

1.3 Is-Signed — Signedness of propagated data type IsSigned1 or IsSigned2 (default) | IsSigned1 | IsSigned2 | TRUE | FALSE

Dependencies

Programmatic Use

1.4.1 Number-of-bits: Base — Number of bits for the base of the propagated data type max([NumBits1 NumBits2]) (default) | NumBits1 | NumBits2 | min([NumBits1 NumBits2]) | NumBits1+NumBits2

Dependencies

Programmatic Use

1.4.2 Number-of-bits: Multiplicative adjustment — Number of bits for multiplicative adjustment of propagated data type 1 (default) | positive integer

Dependencies

Programmatic Use

1.4.3 Number-of-bits: Additive adjustment — Number of bits for additive adjustment of propagated data type 0 (default) | positive integer

Dependencies

Programmatic Use

1.4.4 Number-of-bits: Allowable final values — Allowable number of bits in propagated data type '-1' (default) | scalar or vector of positive integers

Dependencies

Programmatic Use

Propagated Scaling

2. Propagated scaling — Propagated scaling mode Inherit via propagation rule (default) | Specify via dialog | Obtain via best precision

Programmatic Use

2.1. Propagated scaling (Slope, e.g. 2^-9 or [Slope Bias], e.g. [1.25 3]) — Slope or slope and bias 2^-10 | slope | slope and bias in square brackets

Dependencies

Programmatic Use

2.1. Values used to determine best precision scaling — Values to constrain precision [5 -7] (default)

Dependencies

Programmatic Use

Dependencies

Programmatic Use

2.1.2. Slope: Multiplicative adjustment — Slope of multiplicative adjustment of propagated data type 1 (default) | scalar

Dependencies

Programmatic Use

2.1.3. Slope: Additive adjustment — Slope of additive adjustment of propagated data type 0 (default) | scalar

Dependencies

Programmatic Use

2.2.1. Bias: Base — Base bias for Prop Bias1 (default) | Bias2 | max([Bias1 Bias2]) | min([Bias1 Bias2]) | Bias1*Bias2 | Bias1/Bias2 | Bias1+Bias2 | Bias1-Bias2

Dependencies

Programmatic Use

2.2.2. Bias: Multiplicative adjustment — Multiplicative bias for propagated data type 1 (default) | scalar

Programmatic Use

2.3.2. Bias: Additive adjustment — Additive bias for propagated data type 0 (default) | scalar

Dependencies

Programmatic Use

Block Characteristics

Extended Capabilities

C/C++ Code Generation Generate C and C++ code using Simulink® Coder™.

HDL Code Generation Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

Fixed-Point Conversion Design and simulate fixed-point systems using Fixed-Point Designer™.

Version History

See Also

Topics

Ref1 — First reference signal
scalar | vector | matrix | N-D array

Ref2 — Second reference signal
scalar | vector | matrix | N-D array

Prop — Propagated data type and scaling
data type and scaling

1. Propagated data type — Mode of specifying propagated data type
`Inherit via propagation rule` (default) | `Specify via dialog`

1.1. Propagated data type (e.g. fixdt(1,16), fixdt('single')) — Propagated data type
`fixdt(1,16)` (default) | data type string

1.1 If any reference input is double, output is — Output data type when a reference input is double
`double` (default) | `single`

1.2 If any reference input is single, output is — Output data type when a reference input is single
`single` (default) | `double`

1.3 Is-Signed — Signedness of propagated data type
`IsSigned1 or IsSigned2` (default) | `IsSigned1` | `IsSigned2` | `TRUE` | `FALSE`

1.4.1 Number-of-bits: Base — Number of bits for the base of the propagated data type
`max([NumBits1 NumBits2])` (default) | `NumBits1` | `NumBits2` | `min([NumBits1 NumBits2])` | `NumBits1+NumBits2`

1.4.2 Number-of-bits: Multiplicative adjustment — Number of bits for multiplicative adjustment of propagated data type
`1` (default) | positive integer

1.4.3 Number-of-bits: Additive adjustment — Number of bits for additive adjustment of propagated data type
`0` (default) | positive integer

1.4.4 Number-of-bits: Allowable final values — Allowable number of bits in propagated data type
`'-1'` (default) | scalar or vector of positive integers

2. Propagated scaling — Propagated scaling mode
`Inherit via propagation rule` (default) | `Specify via dialog` | `Obtain via best precision`

2.1. Propagated scaling (Slope, e.g. 2^-9 or [Slope Bias], e.g. [1.25 3]) — Slope or slope and bias
`2^-10` | slope | slope and bias in square brackets

2.1. Values used to determine best precision scaling — Values to constrain precision
`[5 -7]` (default)

2.1.2. Slope: Multiplicative adjustment — Slope of multiplicative adjustment of propagated data type
`1` (default) | scalar

2.1.3. Slope: Additive adjustment — Slope of additive adjustment of propagated data type
`0` (default) | scalar

2.2.1. Bias: Base — Base bias for Prop
`Bias1` (default) | `Bias2` | `max([Bias1 Bias2])` | `min([Bias1 Bias2])` | `Bias1*Bias2` | `Bias1/Bias2` | `Bias1+Bias2` | `Bias1-Bias2`

2.2.2. Bias: Multiplicative adjustment — Multiplicative bias for propagated data type
`1` (default) | scalar

2.3.2. Bias: Additive adjustment — Additive bias for propagated data type
`0` (default) | scalar

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.