computer algorithm Books

# List of algorithms Mirror

## List of algorithms Mirror

List of algorithms Mirror

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##### Similar Books

Design and Analysis of Algorithms Course Notes

This note explains core material in data structures and algorithm design, and also helps students prepare for research in the field of algorithms. Topics covered includes: Splay Trees, Amortized Time for Splay Trees, Maintaining Disjoint Sets, Binomial heaps, F-heap, Minimum Spanning Trees, Fredman-Tarjan MST Algorithm, Light Approximate Shortest Path Trees, Matchings, Hopcroft-Karp Matching Algorithm, Two Processor Scheduling, Network Flow - Maximum Flow Problem, The Max Flow Problem and Max-Flow Algorithm.

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Skiena's Algorithms Lectures

This note covers the following topics: Introduction to Algorithms, Asymptotic Notation, Modeling or Logarithms, Elementary Data Structures, Dictionary data structures, Sorting, Heapsort or Priority Queues, Recurrence Relations, Introduction to NP-completeness, Reductions, Cook's Theorem or Harder Reduction, NP-completeness challenge, Approximation Algorithms and Heuristic Methods.

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Data Structures and Algorithms The Basic Toolbox

This book is a concise introduction to this basic toolbox, intended for students and professionals familiar with programming and basic mathematical language.

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Lecture Notes Introduction to Computer Algorithms

This course note provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems.

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Lecture Notes for Algorithm Analysis and Design (PDF 124P)

This note covers the following topics related to Algorithm Analysis and Design: Model and Analysis, Warm up problems, Brute force and Greedy strategy, Dynamic Programming, Searching, Multidimensional Searching and Geometric algorithms, Fast Fourier Transform and Applictions, String matching and finger printing, Graph Algorithms, NP Completeness and Approximation Algorithms.

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Algorithms (Shai Simonson)

This note covers the design of algorithms according to methodology and application. Methodologies include: divide and conquer, dynamic programming, and greedy strategies. Applications involve: sorting, ordering and searching, graph algorithms, geometric algorithms, mathematical (number theory, algebra and linear algebra) algorithms, and string matching algorithms.

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Introduction to Complexity Theory (Oded Goldreich)

This book explains the following topics: intrinsic complexity of computational tasks, Computational Complexity, P, NP, and NP-Completeness, relations between various computational phenomena.

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An Introduction to Computational Complexity

This note covers the following topics: Computational Models, Complexity measures, Power increasing resourses, Basic relatton amomg the models and measures, Reducibility, completeness and closure under reductions, Deterministics and nondeterministics logarithmic space, Deterministics polynomial time, Polynomial Hierarchy and Polynomial space.

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Computer Animation Algorithms Techniques (Rick Parent)

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Lecture Notes on Computational Complexity (Luca Trevisan)

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