The following fixed-point Simulink^{®} blocks provide a mode for scaling parameters whose values are constant vectors or matrices:
This scaling mode is based on binary-point-only scaling. Using this mode, you can scale a constant vector or matrix such that a common binary point is found based on the best precision for the largest value in the vector or matrix.
Constant scaling for best precision is available only for fixed-point data types with unspecified scaling. All other fixed-point data types use their specified scaling. You can use the Data Type Assistant (see Specify Data Types Using Data Type Assistant) on a block dialog box to enable the best precision scaling mode.
On a block dialog box, click the Show data type assistant button .
The Data Type Assistant appears.
In the Data Type Assistant, and
from the Mode list, select Fixed
point
.
The Data Type Assistant displays additional options associated with fixed-point data types.
From the Scaling list, select Best
precision
.
To understand how you might use this scaling mode, consider a 3-by-3 matrix of doubles, M, defined as
3.3333e-003 3.3333e-004 3.3333e-005 3.3333e-002 3.3333e-003 3.3333e-004 3.3333e-001 3.3333e-002 3.3333e-003
Now suppose you specify M as the value of the Gain parameter for a Gain block. The results of specifying your own scaling versus using the constant scaling mode are described here:
Specified Scaling
Suppose the matrix elements are converted to a signed, 10-bit
generalized fixed-point data type with binary-point-only scaling of 2
^{-7} (that
is, the binary point is located seven places to the left of the right
most bit). With this data format, M becomes
0 0 0 3.1250e-002 0 0 3.3594e-001 3.1250e-002 0
Note that many of the matrix elements are zero, and for the nonzero entries, the scaled values differ from the original values. This is because a double is converted to a binary word of fixed size and limited precision for each element. The larger and more precise the conversion data type, the more closely the scaled values match the original values.
Constant Scaling for Best Precision
If M is scaled based on its largest matrix value, you obtain
2.9297e-003 0 0 3.3203e-002 2.9297e-003 0 3.3301e-001 3.3203e-002 2.9297e-003
Best precision would automatically select the fraction length that minimizes the quantization error. Even though precision was maximized for the given word length, quantization errors can still occur. In this example, a few elements still quantize to zero.
Simulink data type names must be valid MATLAB^{®} identifiers with less than 128 characters. The data type name provides information about container type, number encoding, and scaling.
You can represent a fixed-point number using the fixed-point scaling equation
$$V\approx \stackrel{~}{V}=SQ+B,$$
where
V is the real-world value.
$$\stackrel{~}{V}$$ is the approximate real-world value.
$$S=F{2}^{E}$$ is the slope.
F is the slope adjustment factor.
E is the fixed power-of-two exponent.
Q is the stored integer.
B is the bias.
For more information, see Scaling.
The following table provides a key for various symbols that appear in Simulink products to indicate the data type and scaling of a fixed-point value.
Symbol | Description | Example | |
---|---|---|---|
Container Type | |||
| Unsigned fixed-point data type |
| |
| Signed fixed-point data type |
| |
| Scaled
Doubles override of an unsigned fixed-point data type ( |
| |
| Scaled
Doubles override of a signed fixed-point data type ( |
| |
Number Encoding | |||
| 10^ |
| |
| Negative |
| |
| Decimal point |
| |
Scaling Encoding | |||
| Slope |
| |
| Bias |
| |
| Fixed exponent (2^) A negative fixed exponent describes the fraction length |
| |
| Slope adjustment factor |
| |
C,c,D, or d | Compressed encoding for Bias
| No example available. For backwards compatibility only. To
identify and replace calls to | |
T or t | Compressed encoding for Slope
| No example available. For backwards compatibility only. To
identify and replace calls to |