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Animated Algorithms - A Hypermedia Learning Environment for Introduction to Algorithms
64,10 €
MIT Press Ltd
Sivumäärä: 250 sivua
Asu: Digitaalinen tallenne, määrittelemätön
Julkaisuvuosi: 1993, 01.10.1993 (lisätietoa)
This hypermedia CD-ROM provides an ideal format for the visual explanation of complex algorithms contained in the text Introduction to Algorithms, by Thomas H. Cormen, Charles E. Leiserson, and Ronald L. Rivest. It contains three complementary components: a hypertext version of the book itself, interactive animations of the most important algorithms, and movies explaining the use of the hypertext interface and the animations. The hypertext, including the figures, is stored in HyperCard stacks. It contains tools for navigation, text annotation, tracking of preexisting links, full-text search, and the adding of links and paths through the document. This enables instructors and students to customize the hypertext easily for classroom and personal use. The animations that are implemented in HyperCard are linked with the hypertext and can be controlled interactively by the user. They also include extensive on-line help, making them self-contained. Some animations include scripting facilities allowing users to program animations of specific data structures. The movies ("talking heads" and demonstrations) provide a way to view noninteractive versions of the algorithm animations.
These are stored on the CD in QuickTime format. Peter Gloor is Research Associate in the Laboratory for Computer Science, and Scott Dynes is a Ph.D candidate in the Eaton Peabody Laboratory, both at the Massachusetts Institute of Technology. Irene Lee was formerly a graduate student at Harvard University. Animated algorithms: Asymptotic Notation. Recursion. Simple Data Structures. Sorting Algorithms and Analysis. Hashing. Binary Trees. Red-Black Trees. Minimum Spanning Trees. Single-Source Shortest Paths. Fibonacci Heaps. Huffman Encoding. Dynamic Programming. Matrix Multiplication. Matrix Inverse. Convex Hull. Genetic Algorithms. Neural Networks.

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ISBN:
9780262570961
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