Matrix ExampleExamples

Description:
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.
Algorithm:
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:
matrixExample.gif
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