So far, several bit allocation principles have been proposed: fixed bit allocation (FBA) [10, 11, 17] simply assigns a fixed number of bits to each feature.
So far, many works [9 11, 14 20] have adopted the bit extraction framework shown in Figure 1, involving two tasks: (1) designing a one-dimensional quantizer and (2) determining the number of quantization bits for every feature.
Figure 1 The bit extraction framework based on the one-dimensional quantization and coding, where D denotes the number of features; b i denotes the number of quantization bits for the ith feature (i = 1,…, D), and S i denotes the output bits.
The key is generated by cascading every bit pattern of each feature.
(3) Quantization process provides 4 binary bits from each coefficient, totally 72 bits for each block.
The hash tables are optimized to store 64-bit integers, 32 bits for each reference position.
I still need information log(26) bits for each character.
PerM encodes each read into two 64 bit words with two bits for each base, that is, A = (0,0), C = (0, 1), G = (1,0) and T = (1,1).
Of course, they're not the only ones who've been champing at the bit for the feature.
Note that a bit for each one of the possible values of each feature is stored.
