For binary features these two schemes are identical.
2.
Here again, CSL does not posit entities, such as binary features, unless they can be shown to have a function.
3.
Early work on speech recognition attempted to make this inference deterministically using logical rules based on binary features extracted from p ( t ).
4.
To give a further example, the system of Chomsky and Halle defines the class of voiceless stops by the specification of two binary features : [-continuant ] and [-voice ].
5.
The simplest way is to add " k " binary features to each sample, where each feature " j " has value one Ng note that certain variants of " k "-means behave similarly to sparse coding algorithms.
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