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Section "Realization based on bloom filters" follows with a bloom filter realization of the aggregation memberships.
The eight bands are selected for comparison with an existing filter realization [3, 7].
The digital filter realization has become a central topic of signal processing studies.
Mapping this filter realization on a highly parallel architecture entailed a shift in the logical representation of the particles.
Input-output or poles sensitivity is widely used to evaluate the resilience of a filter realization to coefficients quantization in an FWL implementation process.
Going further than previous attempts, the present results suggest that the proposed method, in addition to helping designers in determining the number of bits for fixed-point representations, can also aid in defining details about filter realization and structure.
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His polynomial filter realizations using logarithmic representation or distributed arithmetic enabled the use of these filters in practical devices in the 1980s.
A design example is presented to demonstrate the behavior of the optimal normal realizations and to compare them with several well-known digital filter realizations in terms of minimizing the roundoff noise and the error propagation.
"Verification of digital filters" Section gives a brief introduction about digital filter realizations, emphasizing some aspects related to implementation in fixed-point processors, along with state-of-the-art verification schemes presented in the related literature.
Those systems use second order building blocks on their structures, as mentioned in "Fixed-point filters realization" Section.
Many of the selected test cases use second order structures, because such a realization is widely used and can be applied as a building block to form higher-order systems, as referred in "Fixed-point filters realization" Section.
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