Sentence examples for the input string from inspiring English sources

This type of machine produces no output, but instead tells whether or not the input string has a certain property.

We present an on-line algorithm which constructs a parameterized suffix tree in randomized O(n) time, where n is the length of the input string.

We consider on-line construction of the suffix tree for a parameterized string, where we always have the suffix tree of the input string read so far.

The encoding is effectively computable, clearly, so we can chain a decoding machine together with our universal machine u′; on input an acceptable prefix-free string, the decoder will decompose it into the input string, we then decompose the input string into the Gödel number and the input, and run the machine u′ on that pair of inputs.

These functions can extract the topology information of a molecule from the input string, and then store them into the database as a molecule.

Our method increases the performance by a factor of one to two orders of magnitude, compared to previous hardware implementations, depending on the size of the grammar and the input string length.

In this paper, we introduce a new variant of Closest String where the input strings can contain wildcards that can match any letter in the alphabet, and the goal is to find a solution string without wildcards.

Often, in what follows, the input strings to our problem will be referred to as HP strings.

It is an online algorithm; it can process the input strings letter by letter with a guaranteed low time bound for any prefix of the input.

After receiving n letters, the prefixes s0, i  and t0, j  of the input strings were preprocessed for some i, j such that i +  j =  n.

3. We extend our approach to exploit run-length encodings of the input strings, assuming some restrictions on the cost functions.