Many studies have been developed aiming to improve digital filters realizations, recurring to intricate structures and analysing the error´s behaviour. The work presented in this paper analyses the feasibility of fixed-point implementation of classical IIR notch filters (Butterworth, Chebyshev, Bessel and elliptic), and also the effect of the quality factor and normalized cut-off frequency in the number of significant bits necessary to represent the coefficients, to scrutinize the deformations the filters suffer for distinct design specifications.
The work focuses especially in the implementation of power line notch filters used to improve the signal-to-noise ratio in biomedical signals. The obtained results, when quantizing the digital notch filters, show that by applying second order sections decomposition, low-order digital filters may be designed using only part of double precision capabilities, while high-order notch filters with harsh design constrains are implementable using double precision, but only in second-order sections. Thus, it is shown that to optimize computation time in real-time applications, an optimal digital notch filter implementation platform should have variable arithmetic precision.