Multiplier-less and table-less linear approximation for square and square-root
ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
On Euclidean norm approximations
Pattern Recognition
Comments on "On approximating Euclidean metrics by weighted t-cost distances in arbitrary dimension"
Pattern Recognition Letters
Linear combination of norms in improving approximation of Euclidean norm
Pattern Recognition Letters
Linear combination of weighted t-cost and chamfering weighted distances
Pattern Recognition Letters
An approximate logarithmic squaring circuit with error compensation for DSP applications
Microelectronics Journal
Hi-index | 35.68 |
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.