Data Structure and Algorithm Analysis notes-introduction & Chapter 1

The book was written from to, and has been carefully studied for two or three days since.

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Abbreviation of matrix67:

Data Structure and algorithm analysis (Part 1)

Data Structure and algorithm analysis, abbreviated as 5000 (medium)

Data Structure and algorithm analysis (2)

Luo Cong's study notes:Http://www.luocong.com/dsaanotes/

 

AndAlgorithmComparison of Introduction

This book is not as famous as an introduction to algorithms. Its starting point is slightly higher than the introduction to computing, and more than 300 pages is much thinner than the introduction to algorithms.For me, the description of C language and the extensive use of pointers are more false than the introduction of algorithms.CodeIt seems more difficult. However, the routines are well written, which makes the domestic book-breaking situation quite similar ......The content is not as full as the introduction to algorithms, and the content is also refined, but it is also rich.It is biased towards data structures, but it also involves the design of many algorithms.There is a scanned version of PDF on the Internet. The English version of the answer. The introduction to algorithms is estimated to be the pirated version of the first version. However, the answer and learning resources are much richer. After all, they are quite popular.

 We recommend that you have a certain foundation or want to learn the data structure.

 

My learning plan

If you plan to be free, you can skip this chapter in two days and understand the frequently used parts. We hope that you can complete a Rough Study of most of the content by February 10.

 

Chapter 1 notes

 Chapter 1 Introduction

 

This article mainly reviews the used mathematical knowledge, including exponent, logarithm, series, and modulo operations. It introduces mathematical induction and inverse proof methods. It also describes recursion. There is recursion at lastProgramFour rules of design:

1. Baseline: there must be a critical value ......

2. Continuous promotion: that is to say, when recursive calls are made, the solution is pushed to the benchmark.

3. Design Rule: Write recursive calls can run

4. synthetic benefit rule: do not perform repetitive work in recursive calls when solving a problem. For example, when calculating the Fibonacci sequence, if we write fib (n) = fib (n-1) + fib (n-2), repeated computing many times, the complexity of the algorithm has reached the exponential level ......