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Maximum subarray problems arise in many fields, such as genomic sequence analysis and computer vision.. Genomic sequence analysis employs maximum subarray algorithms to identify important biological segments of protein sequences that have unusual properties, by assigning scores to points within the sequence that are positive when a motif to be recognized is present, and negative when it is not ...
The table C shown below, which is generated by the function LCSLength, shows the lengths of the longest common subsequences between prefixes of and . The i {\displaystyle i} th row and j {\displaystyle j} th column shows the length of the LCS between X 1.. i {\displaystyle X_{1..i}} and Y 1.. j {\displaystyle Y_{1..j}} .
This is a special case of subadditive function, if a sequence is interpreted as a function on the set of natural numbers. Note that while a concave sequence is subadditive, the converse is false. For example, randomly assign a 1 , a 2 , . . . {\displaystyle a_{1},a_{2},...} with values in [ 0.5 , 1 ] {\displaystyle [0.5,1]} ; then the sequence ...
Phase-comparison monopulse is a technique used in radio frequency (RF) applications such as radar and direction finding to accurately estimate the direction of arrival of a signal from the phase difference of the signal measured on two (or more) separated antennas [1] or more typically from displaced phase centers of an array antenna.
var m := map(0 → 0, 1 → 1) function fib(n) if key n is not in map m m[n] := fib(n − 1) + fib(n − 2) return m[n] This technique of saving values that have already been calculated is called memoization ; this is the top-down approach, since we first break the problem into subproblems and then calculate and store values.
Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Microarray analysis techniques are used in interpreting the data generated from experiments on DNA (Gene chip analysis), RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes – in many cases, an organism's entire genome – in a ...
The key difference is that subnets can use the same point in the net multiple times and the indexing set of the subnet can have much larger cardinality. Using the more general definition where we do not require monotonicity, a sequence is a subnet of a given sequence, if and only if it can be obtained from some subsequence by repeating its ...
Every norm, seminorm, and real linear functional is a sublinear function.The identity function on := is an example of a sublinear function (in fact, it is even a linear functional) that is neither positive nor a seminorm; the same is true of this map's negation . [5] More generally, for any real , the map ,: {is a sublinear function on := and moreover, every sublinear function : is of this ...