Combinatorics (Wiley Series in Discrete Mathematics and Optimization)

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A mathematical gem� freshly cleaned and polished

This book is intended to be used as the text for a first course in combinatorics. the text has been shaped by two goals, namely, to make complex mathematics accessible to students with a wide range of abilities, interests, and motivations; and to create a pedagogical tool, useful to the broad spectrum of instructors who bring a variety of perspectives and expectations to such a course.

Features retained from the first edition:

• Lively and engaging writing style
• Timely and appropriate examples
• Numerous well-chosen exercises
• Flexible modular format
• Optional sections and appendices

Highlights of Second Edition enhancements:

• Smoothed and polished exposition, with a sharpened focus on key ideas
• Expanded discussion of linear codes
• New optional section on algorithms
• Greatly expanded hints and answers section
• Many new exercises and examples

Combinatorics (Wiley Series in Discrete Mathematics and Optimization) Review

There is no question that combinatorics is becoming more important in the practice of computer science. While some of the most important techniques are covered in discrete mathematics courses, there is not enough breadth or depth in the coverage. As a consequence, one of my goals this upcoming year is to convince my colleagues at Mount Mercy to add a course in combinatorics to the curriculum. As part of the proposal, I need to create a list of resources and a sample schedule of topics to be covered. To begin this process, I studied several combinatorics texts and decided that this one was the best.
There are six chapters, and the titles are:

 Chapter 1 The mathematics of choice
=623; Chapter 2 The combinatorics of finite functions
 Chapter 3 Polya's theory of enumeration
᠒3; Chapter 4 Generating functions
1623; Chapter 5 Enumeration in graphs
 Chapter 6 Codes and designs

The coverage is thorough and the sequence has been structured to make the last four chapters independent. This necessitated the duplication of some definitions and theorems, but it is a sensible strategy. There is more than enough material for a one-semester course, so this increases the options available to an instructor. I often skip chapters in a textbook in order to cover a topic I consider critical and find it very helpful when the author repeats key definitions and theorems.
The style is mathematically rigorous, the approach is that of a mathematics textbook with the sequence being: theorem, proof, example(s). A large number of exercises are given at the end of each section and solutions/hints to the odd numbered ones are included. It is a sound combinatorics text and the one that I would most likely use if I ever teach such a course.

Published in Journal of Recreational Mathematics, reprinted with permission.

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A Companion to Ancient Macedonia (Blackwell Companions to the Ancient World)

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The most comprehensive and up-to-date work available on ancient Macedonian history and material culture, A Companion to Ancient Macedonia is an invaluable reference for students and scholars alike.

• Features new, specially commissioned essays by � leading and up-and-coming scholars in the field
• Examines the political, military, social, economic, and cultural history of ancient Macedonia from the Archaic period to the end of Roman period and beyond
• Discusses the importance of art, archaeology and architecture
• All ancient sources are translated in English
• Each chapter includes bibliographical essays for further reading

A Companion to Ancient Macedonia (Blackwell Companions to the Ancient World) Review

Elias Kapetanopoulos, Professor Dr., Emeritus

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Computational Intelligence Paradigms: Theory & Applications using MATLAB

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Offering a wide range of programming examples implemented in MATLAB ® , Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi� �Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization. Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

Computational Intelligence Paradigms: Theory & Applications using MATLAB Review

While this book's technical content (e.g. neural net discussion) is quite good, I can't believe that the editor allowed such poor language to pass through the editing process. This book is probably the best example of the kind of linguistic degradation that George Orwell mentioned in "Politics and the English Language." Virtually every sentence contains pseudo-sophisticated words that appear to have been picked at random from a thesaurus. Synonyms usually convey a meaning similar, but not identical to, the original, but the authors never grasped this basic observation. Also, the authors seem not to understand the context in which a given word usually appears, thereby making pretty comical errors that distract the reader. Staying focused on the technical content while processing the linguistic gibberish is quite a challenge.

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Computational Models for Neuroscience: Human Cortical Information Processing

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Understanding how the human brain represents, stores, and processes information is one of the greatest unsolved mysteries of science today. The cerebral cortex is the seat of most of the mental capabilities that distinguish humans from other animals and, once understood, it will almost certainly lead to a better knowledge of other brain nuclei. Although neuroscience research has been underway for 150 years, very little progress has been made. What is needed is a key concept that will trigger a full understanding of existing information, and will also help to identify future directions for research. This book aims to help identify this key concept. Including contributions from leading experts in the field, it provides an overview of different conceptual frameworks that indicate how some pieces of the neuroscience puzzle fit together. It offers a representative selection of current ideas, concepts, analyses, calculations and computer experiments, and also looks at important advances such as the application of new modeling methodologies. Computational Models for Neuroscience will be essential reading for anyone who needs to keep up-to-date with the latest ideas in computational neuroscience, machine intelligence, and intelligent systems. It will also be useful background reading for advanced undergraduates and postgraduates taking courses in neuroscience and psychology.

Computational Models for Neuroscience: Human Cortical Information Processing Review

Chapter 4 of this book is the pot of gold: A concrete, detailed description of how the cerebral cortex works. Thinking relies upon an operation which could be called confabulation (in the chapter it is called concensus building). THIS IS NOT REASONING (at least in any classical sense). Yet, because the simple kind of knowledge used (antecedent support probabilities) is exhaustive, concensus building yields excellent conclusions. This cortical theory also shows why AI has failed: reasoning is too difficult and requires too much knowledge of an expensive type. Cortex gets by with a much simpler type of knowledge (which only concerns pairs of object and action attributes, not n-tuples) which, while it is needed in huge quantities, is easy to obtain. An implication of this corticl theory is that we can now proceed to develop successful AI by adopting this cortical design. The theory is illustrated by means of computer thinking experiments that yield compelling results (and which readers can replicate).

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Computational Nanotechnology: Modeling and Applications with MATLAB? (Nano and Energy)

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Applications of nanotechnology continue to fuel significant innovations in areas ranging from electronics, microcomputing, and biotechnology to medicine, consumer supplies, aerospace, and energy production. As progress in nanoscale science and engineering leads to the continued development of advanced materials and new devices, improved methods of modeling and simulation are required to achieve a more robust quantitative understanding of matter at the nanoscale. Computational Nanotechnology: Modeling and Applications with MATLAB � provides expert insights into current and emerging methods, opportunities, and challenges associated with the computational techniques involved in nanoscale research. Written by, and for, those working in the interdisciplinary fields that comprise nanotechnology—including engineering, physics, chemistry, biology, and medicine� this book covers a broad spectrum of technical information, research ideas, and practical knowledge. It presents an introduction to computational methods in nanotechnology, including a closer look at the theory and modeling of two important nanoscale systems: molecular magnets and semiconductor quantum dots. Topics covered include: Modeling of nanoparticles and complex nano and MEMS systems Theory associated with micromagnetics Surface modeling of thin films Computational techniques used to validate hypotheses that may not be accessible through traditional experimentation Simulation methods for various nanotubes and modeling of carbon nanotube and silicon nanowire transistors In regard to applications of computational nanotechnology in biology, contributors describe tracking of nanoscale structures in cells, effects of various forces on cellular behavior, and use of protein-coated gold nanoparticles to better understand protein-associated nanomaterials. Emphasizing the importance of MATLAB for biological simulations in nanomedicine, this wide-ranging survey of computational nanotechnology concludes by discussing future directions in the field, highlighting the importance of the algorithms, modeling software, and computational tools in the development of efficient nanoscale systems.

Computational Nanotechnology: Modeling and Applications with MATLAB? (Nano and Energy) Review

This is the best book on the market for computational nanotechnology.The book has many applications in Biology, electronics, aerospace, energy productions, and madicine.

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Computational Techniques of the Simplex Method (International Series in Operations Research & Management Science)

You looking to find the "Computational Techniques of the Simplex Method (International Series in Operations Research & Management Science)" Good news! You can purchase Computational Techniques of the Simplex Method (International Series in Operations Research & Management Science) with secure price and compare to view update price on this product. And deals on this product is available only for limited time.

   

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Computational Techniques of the Simplex Method is a systematic treatment focused on the computational issues of the simplex method. It provides a comprehensive coverage of the most important and successful algorithmic and implementation techniques of the simplex method. It is a unique source of essential, never discussed details of algorithmic elements and their implementation. On the basis of the book the reader will be able to create a highly advanced implementation of the simplex method which, in turn, can be used directly or as a building block in other solution algorithms.

Computational Techniques of the Simplex Method (International Series in Operations Research & Management Science) Review

If you are interested in how the Simplex method is actually implemented in commercial scale solvers, this book is a great reference, with discussions of many details of the algorithms. You will need some background on linear algebra and the theory of Simplex: this is not a beginner's tutorial. Simplex is not the only modern commercial technology for linear solving but the dual simplex is the workhorse of daily use because of its efficient restart which is essential for solving integer problems. You will finish this book with a good appreciation of what goes into a modern linear Simplex solver.

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