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This paper proposes an approach for designing a general two-band, FIR, critically sampled, rational rate filter bank (RFB) with perfect reconstruction (PR) and regularity properties.
However, the chemostat approach might have excluded the detection of subpopulations with different protein contents because this 'growth rate filter' was installed.
Next we examined how changes to the firing rate filter time-constant, τ, or the integral time-constant, T i affected control performance.
Several additional filters were also applied to minimize false positive rate: Filter 1 Variants were removed if they are supported by less than two reads or mistakenly called with a probability greater than 0.01.
The false discovery rate filter with an experiment significance level of 0.01 was applied to account for the fact that we are testing the significance of over 500 maps and the result may contain some false positives.
DOI: http://dx.doi.org/10.7554/eLife.07192.012 We explored the parametic sensitivity of the controller by changing the value of either the proportional gain (K), the integral-error time constant (T i ), or the firing rate filter time constant, while the remaining two parameters were held at their nominal values (K = 0.1, T i = 1 s, τ = 2.5 s).
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They make to achieve the adaptive rate sampling (only relevant samples to process) along with the adaptive rate filtering (only relevant operations to deliver a filtered sample).
Two novel adaptive rate filtering techniques have been devised.
It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering.
In [15], 5 scale filters and 12 rate filters were applied for 128 subbands resulting in a feature vector with 7680 elements.
From (14), (15), and (16), it is clear that there are uncommon operations between the classical and the proposed adaptive rate filtering techniques.
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CEO of Professional Science Editing for Scientists @ prosciediting.com