Fundamental Algorithms
... As a variant of this algorithm we could return the index of the data item if we have a match instead of “true” and return −1 in the case of “value not found”. This makes it easier to refer later to the data element. As time complexity we have for each data item mainly one compare and one index incre ...
... As a variant of this algorithm we could return the index of the data item if we have a match instead of “true” and return −1 in the case of “value not found”. This makes it easier to refer later to the data element. As time complexity we have for each data item mainly one compare and one index incre ...
Operations on general linear lists
... Complex ADTs Although several simple ADTs, such as integer, real, character, pointer and so on, have been implemented and are available for use in most languages, many useful complex ADTs are not. As we will see in this chapter, we need a list ADT, a stack ADT, a queue ADT and so on. To be efficien ...
... Complex ADTs Although several simple ADTs, such as integer, real, character, pointer and so on, have been implemented and are available for use in most languages, many useful complex ADTs are not. As we will see in this chapter, we need a list ADT, a stack ADT, a queue ADT and so on. To be efficien ...
Data Structures - Computer Science
... •Thus, we will have 2(i/2)=i cyber-dollars saved at then end of phase i which we can use to double the array size for phase ...
... •Thus, we will have 2(i/2)=i cyber-dollars saved at then end of phase i which we can use to double the array size for phase ...
Partially Persistent Data Structures of Bounded Degree with
... pointer machine model, i.e. they consist of records with a constant number of fields each containing a unit of data or a pointer to another record. The data structures can be viewed as graphs with bounded out-degree. In the following let d denote this bound. The main assumption is that the data stru ...
... pointer machine model, i.e. they consist of records with a constant number of fields each containing a unit of data or a pointer to another record. The data structures can be viewed as graphs with bounded out-degree. In the following let d denote this bound. The main assumption is that the data stru ...
Document
... Insert (t=0, “set X(x)”) changes x value It is known that computing an arbitrary polynomial requires Ω(n) time over any field, even with any infinite subset such as integers, independent of preprocessing of ai in worst case. In “history-independent algebraic decision tree,” the same result holds for ...
... Insert (t=0, “set X(x)”) changes x value It is known that computing an arbitrary polynomial requires Ω(n) time over any field, even with any infinite subset such as integers, independent of preprocessing of ai in worst case. In “history-independent algebraic decision tree,” the same result holds for ...
Use of Voronoi-based hierarchies in WSN (re)
... data and space abstractions can be used to represent Voronoi Cell based partitions of the sensing field and use Voronoi Trees to efficiently map the hierarchical abstractions for energy-efficient processing. The proposed scheme is simulated on the SidNET, a JiST/SWANS based sensor network simulation ...
... data and space abstractions can be used to represent Voronoi Cell based partitions of the sensing field and use Voronoi Trees to efficiently map the hierarchical abstractions for energy-efficient processing. The proposed scheme is simulated on the SidNET, a JiST/SWANS based sensor network simulation ...
Lecture 21
... • Pick an edge e1 = (u, v) in that tree that’s not in Kruskal’s. • Consider the point in Kruskal’s algorithm where u’s set and v’s set were about to be connected. Kruskal selected some edge to connect them: call it e2 . • But, e2 must have at most the same cost as e1 (otherwise Kruskal would have se ...
... • Pick an edge e1 = (u, v) in that tree that’s not in Kruskal’s. • Consider the point in Kruskal’s algorithm where u’s set and v’s set were about to be connected. Kruskal selected some edge to connect them: call it e2 . • But, e2 must have at most the same cost as e1 (otherwise Kruskal would have se ...
Faster Cover Trees - University of California, Riverside
... The naive method for computing pnn involves a linear scan of all the data points and takes time θ (n), but many data structures have been created to speed up this process. The kd-tree (Friedman et al., 1977) is probably the most famous. It is simple and effective in practice, but it can only be used ...
... The naive method for computing pnn involves a linear scan of all the data points and takes time θ (n), but many data structures have been created to speed up this process. The kd-tree (Friedman et al., 1977) is probably the most famous. It is simple and effective in practice, but it can only be used ...
VBI-Tree: A Peer-to-Peer Framework for
... routing node maintains an “upside table”, with information about regions covered by each of its ancestors. Additionally, each node needs to keep information about heights of sub-trees rooted at its children. (This is used for the network restructuring process (see 6.1)). VBI-Tree construction employ ...
... routing node maintains an “upside table”, with information about regions covered by each of its ancestors. Additionally, each node needs to keep information about heights of sub-trees rooted at its children. (This is used for the network restructuring process (see 6.1)). VBI-Tree construction employ ...
An Efficient Algorithm for Finding the Support Count of Frequent 1
... Initially number all the items which is present in the transactions from 1 and so on. It is not necessary that the items have to be sorted in the alphabetical order or in any order. If suppose the transactional database which is being considered consist of 15 items then start the numbering from 1 to ...
... Initially number all the items which is present in the transactions from 1 and so on. It is not necessary that the items have to be sorted in the alphabetical order or in any order. If suppose the transactional database which is being considered consist of 15 items then start the numbering from 1 to ...
Red-black tree
... (and is sometimes called a 'phantom' leaf). And we can safely delete it at the end as n will remain a leaf after all operations, as shown above. If both N and its original parent are black, then deleting this original parent causes paths which proceed through N to have one fewer black node than path ...
... (and is sometimes called a 'phantom' leaf). And we can safely delete it at the end as n will remain a leaf after all operations, as shown above. If both N and its original parent are black, then deleting this original parent causes paths which proceed through N to have one fewer black node than path ...
Indexing Structures for Similarity Search in Metric Spaces
... time complexity is O(n2 ). Text strings are usually compared by the edit distance, so-called the Levenstein distance [22]. This measure computes the minimal number of insertions, deletions, and replacements of one character needed to transform one string into another. This distance function can be a ...
... time complexity is O(n2 ). Text strings are usually compared by the edit distance, so-called the Levenstein distance [22]. This measure computes the minimal number of insertions, deletions, and replacements of one character needed to transform one string into another. This distance function can be a ...