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Complex Burst Matrix Solve Using Q-less QR Decomposition

Compute the value of X in the equation A'AX = B for complex-valued matrices using Q-less QR decomposition

Since R2020a

  • Complex Burst Matrix Solve Using Q-less QR Decomposition block

Libraries:
Fixed-Point Designer HDL Support / Matrices and Linear Algebra / Linear System Solvers

Description

The Complex Burst Matrix Solve Using Q-less QR Decomposition block solves the system of linear equations, A'AX = B, using Q-less QR decomposition, where A and B are complex-valued matrices.

When Regularization parameter is nonzero, the Complex Burst Matrix Solve Using Q-less QR Decomposition block solves the matrix equation

[λInA]'[λInA]X=(λ2In+A'A)X=B

where λ is the regularization parameter, A is an m-by-n matrix, and In = eye(n).

Ports

Input

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Rows of matrix A, specified as a vector. A is an m-by-n matrix where m ≥ 2 and mn. 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

Rows of matrix B, specified as a vector. B is an n-by-p matrix where n ≥ 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

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 ready value is 1 (true), the block captures the values at the A(i,:) and B(i,:) input ports. When this value is 0 (false), the block ignores the input samples.

After sending a true validIn signal, there may be some delay before ready is set to false. To ensure all data is processed, you must wait until ready is set to false before sending another true validIn signal.

Data Types: Boolean

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

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Rows of the matrix X, returned as a scalar or vector.

Data Types: single | double | fixed point

Whether the output data is valid, returned as a Boolean scalar. This control signal indicates when the data at the output port X(i,:) is valid. When this value is 1 (true), the block has successfully computed a row of X. When this value is 0 (false), the output data is not valid.

Data Types: Boolean

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.

After sending a true validIn signal, there may be some delay before ready is set to false. To ensure all data is processed, you must wait until ready is set to false before sending another true validIn signal.

Data Types: Boolean

Parameters

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Number of rows in matrix A, 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 and rows in matrix B, 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, specified as a positive integer-valued scalar.

Programmatic Use

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

Regularization parameter, specified as a nonnegative scalar. Small, positive values of the regularization parameter can improve the conditioning of the problem and reduce the variance of the estimates. While biased, the reduced variance of the estimate often results in a smaller mean squared error when compared to least-squares estimates.

Programmatic Use

Block Parameter: regularizationParameter
Type: character vector
Values: real nonnegative scalar
Default: 0

Data type of the output matrix X, specified as fixdt(1,18,14), double, single, fixdt(1,16,0), or as a user-specified data type expression. The type can be specified directly, or expressed as a data type object such as Simulink.NumericType.

Programmatic Use

Block Parameter: OutputType
Type: character vector
Values: 'fixdt(1,18,14)' | 'double' | 'single' | 'fixdt(1,16,0)' | '<data type expression>'
Default: 'fixdt(1,18,14)'

Tips

Use fixed.getQlessQRMatrixSolveModel(A,B) to generate a template model containing a Complex Burst Matrix Solve Using Q-less QR Decomposition block for complex-valued input matrices A and B.

Algorithms

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Extended Capabilities

Version History

Introduced in R2020a

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