Programming_with_C++,_Theory_and_Problem（绝对高清PDF！）下载

weixin_39820535 2019-05-07 03:30:17

适合有一定经验的C++程序员学习！国外的经典教材！
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适合有一定经验的C++程序员学习！国外的经典教材！人格保证，绝对高清！PDF版！

《C++ 模板技术与 STL实战开发》主讲：丁宋涛泛型编程（Generic Programming）是一种全新的程序设计思想，它和STL是现代C++的精髓。可以说，不会STL很难称得上掌握了现代C++编程。STL是一个高效的C++程序库，它被容纳于C++标准程序库（C++ Standard Library）中，该库包含了诸多在计算机科学领域里所常用的基本数据结构和基本算法。为广大C++程序员们提供了一个可扩展的应用框架，高度体现了软件的可复用性。

在实际开发项目中，使用MATLAB的神经网络工具箱和模糊逻辑工具箱设计算法然后用Coder将算法转换为高级语言。然后使用过Coder的用户就知道，一定有部分应用场景需要直接用高级语言编写算法。这本书就是为此目的编写。书是以网页形式组织的，其中ewtoc.htm是目录。主要章节如下。 ------------------------------------------------------------- • Chapter 1 gives you an overview of neural network terminology and nomenclature. You discover that neural nets are capable of solving complex problems with parallel computational architectures. The Hopfield network and feedforward network are introduced in this chapter. • Chapter 2 introduces C++ and object orientation. You learn the benefits of object-oriented programming and its basic concepts. • Chapter 3 introduces fuzzy logic, a technology that is fairly synergistic with neural network problem solving. You learn about math with fuzzy sets as well as how you can build a simple fuzzifier in C++. • Chapter 4 introduces you to two of the simplest, yet very representative, models of: the Hopfield network, the Perceptron network, and their C++ implementations. • Chapter 5 is a survey of neural network models. This chapter describes the features of several models, describes threshold functions, and develops concepts in neural networks. • Chapter 6 focuses on learning and training paradigms. It introduces the concepts of supervised and unsupervised learning, self-organization and topics including backpropagation of errors, radial basis function networks, and conjugate gradient methods. • Chapter 7 goes through the construction of a backpropagation simulator. You will find this simulator useful in later chapters also. C++ classes and features are detailed in this chapter. • Chapter 8 covers the Bidirectional Associative memories for associating pairs of patterns. • Chapter 9 introduces Fuzzy Associative memories for associating pairs of fuzzy sets. • Chapter 10 covers the Adaptive Resonance Theory of Grossberg. You will have a chance to experiment with a program that illustrates the working of this theory. • Chapters 11 and 12 discuss the Self-Organizing map of Teuvo Kohonen and its application to pattern recognition. • Chapter 13 continues the discussion of the backpropagation simulator, with enhancements made to the simulator to include momentum and noise during training. • Chapter 14 applies backpropagation to the problem of financial forecasting, discusses setting up a backpropagation network with 15 input variables and 200 test cases to run a simulation. The problem is approached via a systematic 12-step approach for preprocessing data and setting up the problem. You will find a number of examples of financial forecasting highlighted from the literature. A resource guide for neural networks in finance is included for people who would like more information about this area. • Chapter 15 deals with nonlinear optimization with a thorough discussion of the Traveling Salesperson problem. You learn the formulation by Hopfield and the approach of Kohonen. • Chapter 16 treats two application areas of fuzzy logic: fuzzy control systems and fuzzy databases. This chapter also expands on fuzzy relations and fuzzy set theory with several examples. • Chapter 17 discusses some of the latest applications using neural networks and fuzzy logic.

This book is about the usage of data structures and algorithms in computer programming. Designing an efficient algorithm to solve a computer science problem is a skill of Computer programmer. This is the skill which tech companies like Google, Amazon, Microsoft, Adobe and many others are looking for in an interview. This book assumes that you are a C++ language developer. You are not an expert in C++ language, but you are well familiar with concepts of references, functions, arrays and recursion. In the start of this book, we will be revising the C++ language fundamentals that will be used throughout this book. We will be looking into some of the problems in arrays and recursion too. Then in the coming chapter, we will be looking into complexity analysis. Then will look into the various data structures and their algorithms. We will be looking into a linked list, stack, queue, trees, heap, hash table and graphs. We will be looking into sorting, searching techniques. Then we will be looking into algorithm analysis, we will be looking into brute force algorithms, greedy algorithms, divide and conquer algorithms, dynamic programming, reduction, and backtracking. In the end, we will be looking into the system design that will give a systematic approach for solving the design problems in an Interview. Table of Contents CHAPTER 1: INTRODUCTION - PROGRAMMING OVERVIEW CHAPTER 2: ALGORITHMS ANALYSIS CHAPTER 3: APPROACH TO SOLVE ALGORITHM DESIGN PROBLEMS CHAPTER 4: ABSTRACT DATA TYPE & C++ COLLECTIONS CHAPTER 5: SEARCHING CHAPTER 6: SORTING CHAPTER 7: LINKED LIST CHAPTER 8: STACK CHAPTER 9: QUEUE CHAPTER 10: TREE CHAPTER 11: PRIORITY QUEUE CHAPTER 12: HASH-TABLE CHAPTER 13: GRAPHS CHAPTER 14: STRING ALGORITHMS CHAPTER 15: ALGORITHM DESIGN TECHNIQUES CHAPTER 16: BRUTE FORCE ALGORITHM CHAPTER 17: GREEDY ALGORITHM CHAPTER 18: DIVIDE-AND-CONQUER, DECREASE-AND-CONQUER CHAPTER 19: DYNAMIC PROGRAMMING CHAPTER 20: BACKTRACKING AND BRANCH-AND-BOUND CHAPTER 21: COMPLEXITY THEORY AND NP COMPLETENESS CHAPTER 22: INTERVIEW STRATEGY CHAPTER 23: SYSTEM DESIGN

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