  This paper investigates the impact of different approximation methods in
feature extraction for pattern recognition applications, specifically focused
on delta and delta-delta parameters. Using MCYT330 online signature data-base,
our experiments show that 11-point approximation outperforms 1-point
approximation, resulting in a 1.4% improvement in identification rate, 36.8%
reduction in random forgeries and 2.4% reduction in skilled forgeries
