Title :
A Low Complexity Euclidean Norm Approximation
Author :
Seol, Changkyu ; Cheun, Kyungwhoon
Author_Institution :
Pohang Univ. of Sci. & Technol. (POSTECH), Pohang
fDate :
4/1/2008 12:00:00 AM
Abstract :
The need for real-time computation of the Euclidean norm of a vector arises frequently in many signal processing applications such as vector median filtering, vector quantization and multiple-input multiple-output wireless communication systems. In this correspondence, we examine the properties of a linear combination of the 1-norm and the infinity norm as an approximation to the Euclidean norm of real-valued vectors. The approximation requires only two multiplications regardless of the vector length and does not require sorting of the absolute values of the vector entries. Numerical results show that the considered approximation incurs negligible performance degradations in typical applications.
Keywords :
approximation theory; signal processing; Euclidean norm approximation; infinity norm; signal processing; Euclidean norm approximation; median filtering; multiple-input multiple-output (MIMO); vector quantization;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.909354