Documentation

# Complex Burst QR Decomposition

QR decomposition for complex-valued matrices

## Description

The Complex Burst QR Decomposition block uses QR decomposition to compute R and C = Q'B, where QR = A, and A and B are complex-valued matrices. The least-squares solution to Ax = B is x = R\C. R is an upper triangular matrix and Q is an orthogonal matrix. To compute C = Q', set B to be the identity matrix.

### Creation

`model = fixed.getQRFactorizationModel(A, B)` generates a model named `model` containing a QR Decomposition block and data input matrices, `A` and `B`.

## Ports

### Input

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Rows of matrix A, where A is a m-by-n matrix with m, n ≥ 2. If B is single or double, A must be the same data type as B. If A is fixed point, A must be signed, use binary point scaling, and have the same word length as B. Slope-bias representation is not supported for fixed-point data types.

Data Types: `single` | `double` | `fixed point`
Complex Number Support: Yes

Rows of matrix B, where B is an m-by-p matrix with m ≥ 2. If A is single or double, B must be the same data type as A. If B is fixed point, B must be signed, use binary point scaling, and have the same word length as A. Slope-bias representation is not supported for fixed-point data types.

Data Types: `single` | `double` | `fixed point`
Complex Number Support: Yes

Indicates valid inputs, specified as a `Boolean` scalar. Control signal that indicates when the data from the `A(i,:)` and `B(i,:)` input ports is valid. When this value is 1 (`true`) and ready is 1 (`true`), the block captures the values on the `A(i,:)` and `B(i,:)` input ports. When this value is 0 (`false`), the block ignores the input samples.

Data Types: `Boolean`

Clears internal state, specified as a `Boolean` scalar. When this value is 1 (`true`), the block stops the current calculation and clears all internal states. When this value is 0 (`false`), and the `validIn` value is 1 (`true`), the block begins a new subframe.

Data Types: `Boolean`

### Output

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Rows of the economy sized QR decomposition matrix R. R is an upper triangular matrix. R has the same data type as A.

Data Types: `single` | `double` | `fixed point`

Rows of the economy sized QR decomposition matrix C=Q'B. C has the same number of rows as R. C has the same data type as B.

Data Types: `single` | `double` | `fixed point`

Control signal that indicates when the data at output ports `R(i,:)` and `C(i,:)` is valid. When this value is 1 (`true`), the block has successfully computed the `R` and `C` matrices. When this value is 0 (`false`), the output data is not valid.

Data Types: `Boolean`

Control signal that indicates when the block is ready for new input data. When this value is 1 (`true`), and `validIn` is 1 (`true`), the block accepts input data in the next time step. When this value is 0 (`false`), the block ignores input data in the next time step.

Data Types: `Boolean`

## Parameters

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The number of rows in matrices A and B, specified as a positive integer-valued scalar.

#### Programmatic Use

 Block Parameter: `m` Type: character vector Values: integer-valued scalar Default: `'4'`

The number of columns in input matrix A, specified as a positive integer-valued scalar.

#### Programmatic Use

 Block Parameter: `n` Type: character vector Values: integer-valued scalar Default: `'4'`

The number of columns in input matrix B, specified as a positive integer-valued scalar.

#### Programmatic Use

 Block Parameter: `p` Type: character vector Values: integer-valued scalar Default: `'1'` 