Low-Complexity LS Algorithm Using Coordinate Transformation

To reduce the computational complexity, decrease hardware resource consumption, and make it practicable, we propose a novel coordinate transformation based low-complexity Least squares (LS) algorithm. The positive integral variable is set as a reference coordinate and coefficients are transformed to be constant. The fitting polynomial in the reference coordinate system can be easily realized with lower complexity. To achieve the fitting curve in the original coordinate system, coordinate transformation is needed. Compared with the conventional LS fitting, our implementation results show that the proposed LS fitting algorithm can greatly reduce hardware resources in the premise of meeting the precision requirements.