Complex Burst QR Decomposition
QR decomposition for complex-valued matrices
- Library:
Fixed-Point Designer / Matrices and Linear Algebra / Matrix Factorizations
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
fixed.getQRDecompositionModel(
generates a template model containing a Complex Burst QR Decomposition block
for complex-valued input matrices A and B.A,B)
Ports
Input
A(i,:) — Rows of matrix A
vector
Rows of matrix A, specified as a vector. A is an m-by-n matrix where m ≥ 2 and n ≥ 2. If B is single or double, A must be the same data type as B. If A is a fixed-point data type, 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
B(i,:) — Rows of matrix B
vector
Rows of matrix B, specified as a vector. B is an m-by-p matrix where m ≥ 2. If A is single or double, B must be the same data type as A. If B is a fixed-point data type, 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
validIn — Whether inputs are valid
Boolean scalar
Whether inputs are valid, specified as a Boolean scalar. This control signal
indicates when the data from the A(i,:) and
B(i,:) input ports are valid. When this value is 1
(true) and the value at 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
restart — Whether to clear internal states
Boolean scalar
Whether to clear internal states, 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
R(i,:) — Rows of matrix R
scalar | vector
Rows of the economy size QR decomposition matrix R, returned as a scalar or vector. R is an upper triangular matrix. R has the same data type as A.
Data Types: single | double | fixed point
C(i,:) — Rows of matrix C=Q'B
scalar | vector
Rows of the economy size QR decomposition matrix C=Q'B, returned as a scalar or vector. C has the same number of rows as R. C has the same data type as B.
Data Types: single | double | fixed point
validOut — Whether output data is valid
Boolean scalar
Whether the output data is valid, returned as a Boolean scalar. This control
signal 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
ready — Whether block is ready
Boolean scalar
Whether the block is ready, returned as a Boolean scalar. This control signal
indicates when the block is ready for new input data. When this value is 1
(true), and the validIn value 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
Number of rows in matrices A and B — Number of rows in matrices A and B
4 (default) | positive integer-valued scalar
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: positive integer-valued scalar |
Default:
4 |
Number of columns in matrix A — Number of columns in matrix A
4 (default) | positive integer-valued scalar
The number of columns in input matrix A, specified as a positive integer-valued scalar.
Programmatic Use
Block Parameter:
n |
| Type: character vector |
| Values: positive integer-valued scalar |
Default:
4 |
Number of columns in matrix B — Number of columns in matrix B
1 (default) | positive integer-valued scalar
The number of columns in input matrix B, specified as a positive integer-valued scalar.
Programmatic Use
Block Parameter:
p |
| Type: character vector |
| Values: positive integer-valued scalar |
Default:
1 |
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.
HDL Code Generation
Generate Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.
HDL Coder™ provides additional configuration options that affect HDL implementation and synthesized logic.
This block has a single, default HDL architecture.
| General | |
|---|---|
| ConstrainedOutputPipeline | Number of registers to place at
the outputs by moving existing delays within your design. Distributed
pipelining does not redistribute these registers. The default is
|
| InputPipeline | Number of input pipeline stages
to insert in the generated code. Distributed pipelining and constrained
output pipelining can move these registers. The default is
|
| OutputPipeline | Number of output pipeline stages
to insert in the generated code. Distributed pipelining and constrained
output pipelining can move these registers. The default is
|
Supports fixed-point data types only.
Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.
A and B must be signed, use binary-point scaling, and have the same word length. Slope-bias representation is not supported for fixed-point data types.
See Also
Blocks
- Complex Burst Q-less QR Decomposition | Complex Partial-Systolic QR Decomposition | Real Burst QR Decomposition