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Image of Introduction to Algorithms
Penanda Bagikan

e-book

Introduction to Algorithms

Thomas H. Cormen [et.al] - Nama Orang;

We hope that this textbook provides you with an enjoyable introduction to the
field of algorithms. We have attempted to make every algorithm accessible and
interesting. To help you when you encounter unfamiliar or difficult algorithms, we
describe each one in a step-by-step manner. We also provide careful explanations
of the mathematics needed to understand the analysis of the algorithms. If you
already have some familiarity with a topic, you will find the chapters organized so
that you can skim introductory sections and proceed quickly to the more advanced
material.

This is a large book, and your class will probably cover only a portion of its
material. We have tried, however, to make this a book that will be useful to you
now as a course textbook and also later in your career as a mathematical desk
reference or an engineering handbook.

What are the prerequisites for reading this book?
* You should have some programming experience. In particular, you should understand
recursive procedures and simple data structures such as arrays and
linked lists.
* You should have some facility with mathematical proofs, and especially proofs
by mathematical induction. A few portions of the book rely on some knowledge
of elementary calculus. Beyond that, Parts I and VIII of this book teach you all
the mathematical techniques you will need.


Ketersediaan

Tidak ada salinan data

Informasi Detail
Judul Seri
-
No. Panggil
-
Penerbit
London : Massachusetts Institute of Technology., 2009
Deskripsi Fisik
QA76.6.I5858; 005.1—dc22
Bahasa
English
ISBN/ISSN
978-0-262-53305-8
Klasifikasi
-
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
3rd ed.
Subjek
MATEMATIKA
Info Detail Spesifik
-
Pernyataan Tanggungjawab
agus
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • FRONT MATTER
  • CONTENTS
  • 1 The Role of Algorithms in Computing
  • 2 Getting Started
  • 3 Growth of Functions
  • 4 Divide-and-Conquer
  • 5 Probabilistic Analysis and Randomized Algorithms
  • 6 Heapsort
  • 7 Quicksort
  • 8 Sorting in Linear Time
  • 9 Medians and Order Statistics
  • 10 Elementary Data Structures
  • 11 Hash Tables
  • 12 Binary Search Trees
  • 13 Red-Black Trees
  • 14 Augmenting Data Structures
  • 15 Dynamic Programming
  • 16 Greedy Algorithms
  • 17 Amortized Analysis
  • 18 B-Trees
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