CMSIS-DSP  Version 1.5.2
CMSIS DSP Software Library
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Matrix Example
Demonstrates the use of Matrix Transpose, Matrix Muliplication, and Matrix Inverse functions to apply least squares fitting to input data. Least squares fitting is the procedure for finding the best-fitting curve that minimizes the sum of the squares of the offsets (least square error) from a given set of data.
The linear combination of parameters considered is as follows:
A * X = B, where X is the unknown value and can be estimated from A & B.
The least squares estimate X is given by the following equation:
X = Inverse(AT * A) * AT * B
Block Diagram:
Variables Description:
  • A_f32 input matrix in the linear combination equation
  • B_f32 output matrix in the linear combination equation
  • X_f32 unknown matrix estimated using A_f32 & B_f32 matrices
CMSIS DSP Software Library Functions Used:

Refer arm_matrix_example_f32.c