Store 
| Products & Services | Solutions | Academia | Support | User Community | Company |
 |
Download Product Updates | | |  |
Get Pricing | | | |
Trial Software |
| Documentation → Signal Processing Blockset |
| Products & Services | Solutions | Academia | Support | User Community | Company |
|
Download Product Updates | | | |
Get Pricing | | | |
Trial Software |
| Documentation → Signal Processing Blockset |
| Contents | Index |
| Learn more about Signal Processing Blockset |
Math Functions / Math Operations
dspmathops
The Normalization block independently normalizes each row, column, or vector of the specified dimension of the input. The Normalization block accepts real and complex floating-point and fixed-point inputs except for complex unsigned fixed-point inputs. The block only accepts floating-point signals for the 2-norm mode, and both fixed-point and floating-point signals for the squared 2-norm mode. The output always has the same dimensions and frame status as the input.
This block treats an arbitrarily dimensioned input U as a collection of vectors oriented along the specified dimension. The block normalizes these vectors by either their norm or the square of their norm.
For example, consider a 3-dimensional input U(i,j,k) and assume that you want to normalize along the second dimension. First, define the 2-dimensional intermediate quantity V(i,k) such that each element of V is the norm of one of the vectors in U:
Given V, the output of the block Y(i, j,k) in 2-norm mode is
In squared 2-norm mode, the block output is
The normalization bias, b, is typically chosen to be a small positive constant (for example, 1e-10) that prevents potential division by zero.
The following diagram shows the data types used within the Normalization block for fixed-point signals (squared 2-norm mode only).
The output of the multiplier is in the product output data type when the input is real. When the input is complex, the result of the multiplication is in the accumulator data type. For details on the complex multiplication performed, see Multiplication Data Types. You can set the accumulator, product output, and output data types in the block dialog as discussed in Dialog Box.
See Zero Algorithmic Delay in the Signal Processing Blockset User's Guide for an example.
The Main pane of the Normalization dialog appears as follows.
Specify the type of normalization to perform, 2-norm or Squared 2-norm. 2-norm mode supports floating-point signals only. Squared 2-norm supports both fixed-point and floating-point signals.
Specify the real value b to be added in the denominator to avoid division by zero. Tunable.
Specify whether to normalize along rows, columns, or the dimension specified in the Dimension parameter.
Specify the one-based value of the dimension over which to normalize. The value of this parameter cannot exceed the number of dimensions in the input signal. This parameter is only visible if Specified dimension is selected for the Normalize over parameter.
Select to treat a sample-based row input as a column.
The Data type attributes pane of the Normalization dialog appears as follows.
Note The parameters on this pane are only applicable to fixed-point signals when the block is in squared 2-norm mode. See Fixed-Point Data Types for a diagram of how the product output, accumulator, and output data types are used in this case. |
Select the rounding mode for fixed-point operations.
Select the overflow mode for fixed-point operations.
Specify the product output data type. See Fixed-Point Data Types and Multiplication Data Types for illustrations depicting the use of the product output data type in this block. You can set it to:
A rule that inherits a data type, for example, Inherit: Same as input
An expression that evaluates to a valid data type, for example, fixdt([],16,0)
Click the Show data type assistant button
to display the Data
Type Assistant, which helps you set the Product
output data type parameter.
See Using the Data Type Assistant for more information.
Specify the accumulator data type. See Fixed-Point Data Types for illustrations depicting the use of the accumulator data type in this block. You can set this parameter to:
A rule that inherits a data type, for example, Inherit: Same as product output
An expression that evaluates to a valid data type, for example, fixdt([],16,0)
Click the Show data type assistant button
to display the Data
Type Assistant, which helps you set the Accumulator
data type parameter.
See Using the Data Type Assistant for more information.
Specify the output data type. See Fixed-Point Data Types for illustrations depicting the use of the output data type in this block. You can set it to:
A rule that inherits a data type, for example, Inherit: Same as product output
An expression that evaluates to a valid data type, for example, fixdt([],16,0)
Click the Show data type assistant button
to display the Data
Type Assistant, which helps you set the Output
data type parameter.
See Specifying Block Output Data Types for more information.
Specify the minimum value that the block should output. The default value, [], is equivalent to -Inf. Simulink software uses this value to perform:
Simulation range checking (see Checking Signal Ranges)
Automatic scaling of fixed-point data types
Specify the maximum value that the block should output. The default value, [], is equivalent to Inf. Simulink software uses this value to perform:
Simulation range checking (see Checking Signal Ranges)
Automatic scaling of fixed-point data types
Select this parameter to prevent any fixed-point scaling you specify in this block mask from being overridden by the autoscaling tool in the Fixed-Point Tool.
| Port | Supported Data Types |
|---|---|
Input |
|
Output |
|
| Array-Vector Multiply | Signal Processing Blockset |
| Reciprocal Condition | Signal Processing Blockset |
| norm | MATLAB |
 | NCO | Nyquist Filter |  |
Learn more about Simulink through this collection of videos, articles, technical literature and the Getting Started with Simulink Guide.
| © 1984-2009- The MathWorks, Inc. - Site Help - Patents - Trademarks - Privacy Policy - Preventing Piracy - RSS |
