Abstrakt
Many studies have been developed aiming to improve digital filters
realizations, recurring to intricate structures and analyzing
probabilistically the error's behavior. The work presented in this paper
analyzes the feasibility of fixed-point implementation of classical
infinite impulse response notch filters: Butterworth, Chebyshev I and II,
and elliptic. To scrutinize the deformations suffered for distinct design
specifications, it is assessed: the effect of the quality factor and
normalized cut-off frequency, in the number of significant bits necessary
to represent the filter's coefficients. The implications brought to FPGA
implementation are also verified.
The work focuses especially on the implementation of power line notch filters
used to improve the signal-to-noise ratio in biomedical signals. The
results obtained, 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.
High-order notch filters with harsh design constraints are implementable
using double precision, but only in second-order sections. Thus, it is
revealed that to optimize computation time in real-time applications, an
optimal digital notch filter implementation platform should have variable
arithmetic precision.
Considering these implementation constraints, utmost operation performance is
finally estimated when implementing digital notch filters in Xilinx
Virtex-5 field-programmable gate arrays. The influence of several design
specifications, e.g. type, and order, in the filter's behavior was
evaluated, namely in regard to order, type, input and coefficient number
of bits, quality factor and cut-off frequency. Finally the implications
and potential applications of such results are discussed.
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