In addition to the analysis of the canSNPs that define the A.Br.008/009 sublineage, large portions of the pagA gene sequence were reconstructed from sample 7.RA93.15.15 by using 40 overlapping PCR fragments without whole genome amplification.
Conversely, if can be reconstructed from its samples, it must be true that is bandlimited to, since a sampled signal only supports frequencies up to (see §D.4 below).
Traditional signal processing approaches for sensing and processing of information have relied on the Shannon sampling theorem, which states that a bandlimited signal x t) can be reconstructed from uniform samples {x kT s )}: x ( t ) = ∑ k x ( k T s ) sin ( Ω max ( t - k T s ) / π ) Ω max ( t - k T s ) / π (1).
Some of the coolest questions in our field are about optimization over input that is kept by selfish agents ("mechanism design"), depends on future events ("online algorithms"), or has to be reconstructed from noisy samples ("machine learning").
Then, the original input signal x t) can be reconstructed from the samples of the N outputs g k (t) of the LCT filters H k M u.
Multichannel sampling theorem in the LCT domain states that a bandlimited signal in the LCT domain can be reconstructed from the samples of the outputs of multiple LCT filters [26].
For a bandlimited graph signal, the unknown data associated with unsampled vertices can be reconstructed from the sampled data by exploiting the spatial relationship of graph signal.
It states that any f ∈ B τ can be reconstructed from its sampled values f ( x k ), where x k = k π / τ and k ∈ Z, by the formula f ( x ) = ∑ k ∈ Z f ( x k ) sinc ( τ x / π − k ), x ∈ R, (1.2).
Under these conditions the signal can be reconstructed from the uniform samples according to the following sinc interpolation: (1).
The DC, 1 f amplitude and 1 f phase can be reconstructed from the four samples, S n, using a standard phase stepping algorithm (Fairbairn et al., 2012) shown in Eqs.
