Data Structures and Algorithms - Cambridge Computer Laboratory
... Manber, “Introduction to Algorithms” is strong on motivation, case sudies and exercises. Salomon, “Data Compression” is published by Springer and gives a good introduction to many data compression methods including the BurrowsWheeler algorithm. Your attention is also drawn to Graham, Knuth and Patas ...
... Manber, “Introduction to Algorithms” is strong on motivation, case sudies and exercises. Salomon, “Data Compression” is published by Springer and gives a good introduction to many data compression methods including the BurrowsWheeler algorithm. Your attention is also drawn to Graham, Knuth and Patas ...
Cache-Oblivious Algorithms and Data Structures
... has several surprisingly powerful consequences. One consequence is that, if a cache-oblivious algorithm performs well between two levels of the memory hierarchy (nominally called cache and disk), then it must automatically work well between any two adjacent levels of the memory hierarchy. This conse ...
... has several surprisingly powerful consequences. One consequence is that, if a cache-oblivious algorithm performs well between two levels of the memory hierarchy (nominally called cache and disk), then it must automatically work well between any two adjacent levels of the memory hierarchy. This conse ...
TRIANGULATING POLYGONS WITHOUT LARGE ANGLES 1
... lines. Let b = s=8. Imagine the plane divided into an in nite square grid with spacing b. Each vertex of P 0 falls into a di erent square in this grid; call these squares occupied . Call a square orthogonally or diagonally adjacent to an occupied square a neighbor square. Erase all lines of the grid ...
... lines. Let b = s=8. Imagine the plane divided into an in nite square grid with spacing b. Each vertex of P 0 falls into a di erent square in this grid; call these squares occupied . Call a square orthogonally or diagonally adjacent to an occupied square a neighbor square. Erase all lines of the grid ...
What is data structure
... A data structure is a way of organizing data that considers not only the items stored, but also their relationship to each other. Advance knowledge about the relationship between data items allows designing of efficient algorithms for the manipulation of data. Definition of data structures • Many al ...
... A data structure is a way of organizing data that considers not only the items stored, but also their relationship to each other. Advance knowledge about the relationship between data items allows designing of efficient algorithms for the manipulation of data. Definition of data structures • Many al ...
7.1. Single- and Double-Ended Priority Queues:
... a) heap-shape: all leaves lie on at most two adjacent levels, and the leaves on the last level occupy the leftmost positions; all other levels are complete. b) max-ordering: the value stored at a node is greater than or equal to the values stored at its children. A max-heap of size n can be construc ...
... a) heap-shape: all leaves lie on at most two adjacent levels, and the leaves on the last level occupy the leftmost positions; all other levels are complete. b) max-ordering: the value stored at a node is greater than or equal to the values stored at its children. A max-heap of size n can be construc ...
The BoND-tree: An Efficient Indexing Method for Box Queries in Non-ordered Discrete Data Spaces, IEEE Transactions on Data and Knowledge Engineering, 2013, Changqing Chen, Alok Watve, Sakti Pramanik, Qiang Zhu
... that work well for similarity queries do not necessarily support box(window) queries efficiently. This is because query conditions for box queries are specified for each dimension separately—any indexed vector which has conflicts with the query condition on any dimension is pruned away immediately f ...
... that work well for similarity queries do not necessarily support box(window) queries efficiently. This is because query conditions for box queries are specified for each dimension separately—any indexed vector which has conflicts with the query condition on any dimension is pruned away immediately f ...
MIT 6.851 Advanced Data Structures
... 17.1 i − 1 and i are on the same level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 17.2 i − 1 and i are different levels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 17.3 Division of bit string into chunks and sub-chunks, as in the rank algorithm . . . . . 14 ...
... 17.1 i − 1 and i are on the same level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 17.2 i − 1 and i are different levels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 17.3 Division of bit string into chunks and sub-chunks, as in the rank algorithm . . . . . 14 ...
Insert after specified number of nodes
... Integers, reals, and booleans have operations associated with them and so do data types such union, intersection, find, size, and complement. Why Linked lists? Let us consider an example of implementation of a STACK or a QUEUE using a linear array then it is necessary to declare the SIZE of the STAC ...
... Integers, reals, and booleans have operations associated with them and so do data types such union, intersection, find, size, and complement. Why Linked lists? Let us consider an example of implementation of a STACK or a QUEUE using a linear array then it is necessary to declare the SIZE of the STAC ...
Lecture8KS
... Really ordered binary trees: every child is either left or right (even when the other child is missing). Information can be stored only at all nodes (for simplicity, let's just say an integer can be stored). Intuitively, it should be clear that this DS is more “powerful” than just linked lists. Righ ...
... Really ordered binary trees: every child is either left or right (even when the other child is missing). Information can be stored only at all nodes (for simplicity, let's just say an integer can be stored). Intuitively, it should be clear that this DS is more “powerful” than just linked lists. Righ ...
Quadtree
A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. A similar partitioning is also known as a Q-tree. All forms of quadtrees share some common features: They decompose space into adaptable cells Each cell (or bucket) has a maximum capacity. When maximum capacity is reached, the bucket splits The tree directory follows the spatial decomposition of the quadtree.