Saturday, January 2, 2010

[G866.Ebook] PDF Ebook Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

PDF Ebook Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

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Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine



Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

PDF Ebook Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

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Game Theory and Learning for Wireless Networks: Fundamentals and Applications, by Samson Lasaulce, Hamidou Tembine

* The first tutorial-style book that gives all the relevant theory at the right level of rigor, for the wireless communications engineer.

* Bridges the gap between theory and practice by giving examples and case studies showing how game theory can solve real-word problems.

* Contains algorithms and techniques to implement game theory in wireless terminals.

Written by leading experts in the field, Game Theory and Learning for Wireless Networks Covers how theory can be used to solve prevalent problems in wireless networks such as power control, resource allocation or medium access control. With the emphasis now on promoting ‘green’ solutions in the wireless field where power consumption is minimized, there is an added focus on developing network solutions that maximizes the use of the spectrum available.

With the growth of distributed wireless networks such as Wi-Fi and the Internet; the push to develop ad hoc and cognitive networks has led to a considerable interest in applying game theory to wireless communication systems. Game Theory and Learning for Wireless Networks is the first comprehensive resource of its kind, and is ideal for wireless communications R&D engineers and graduate students.

Samson Lasaulce is a senior CNRS researcher at the Laboratory of Signals and Systems (LSS) at Sup�lec, Gif-sur-Yvette, France. He is also a part-time professor in the Department of Physics at �cole Polytechnique, Palaiseau, France.

Hamidou Tembine is a professor in the Department of Telecommunications at Sup�lec, Gif-sur-Yvette, France.

Merouane Debbah is a professor at Sup�lec, Gif-sur-Yvette, France. He is the holder of the Alcatel-Lucent chair in flexible radio since 2007.

  • The first tutorial style book that gives all the relevant theory, at the right level of rigour, for the wireless communications engineer
  • Bridges the gap between theory and practice by giving examples and case studies showing how game theory can solve real world resource allocation problems
  • Contains algorithms and techniques to implement game theory in wireless terminals

  • Sales Rank: #3681651 in Books
  • Published on: 2011-10-03
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.30" h x .70" w x 7.50" l, 1.75 pounds
  • Binding: Hardcover
  • 336 pages

From the Back Cover

* The first tutorial-style book that gives all the relevant theory at the right level of rigor, for the wireless communications engineer.

* Bridges the gap between theory and practice by giving examples and case studies showing how game theory can solve real-word problems.

* Contains algorithms and techniques to implement game theory in wireless terminals.

Written by leading experts in the field, Game Theory and Learning for Wireless Networks Covers how theory can be used to solve prevalent problems in wireless networks such as power control, resource allocation or medium access control. With the emphasis now on promoting ‘green’ solutions in the wireless field where power consumption is minimized, there is an added focus on developing network solutions that maximizes the use of the spectrum available.

With the growth of distributed wireless networks such as Wi-Fi and the Internet; the push to develop ad hoc and cognitive networks has led to a considerable interest in applying game theory to wireless communication systems. Game Theory and Learning for Wireless Networks is the first comprehensive resource of its kind, and is ideal for wireless communications R&D engineers and graduate students.

Samson Lasaulce is a senior CNRS researcher at the Laboratory of Signals and Systems (LSS) at Sup�lec, Gif-sur-Yvette, France. He is also a part-time professor in the Department of Physics at �cole Polytechnique, Palaiseau, France.

Hamidou Tembine is a professor in the Department of Telecommunications at Sup�lec, Gif-sur-Yvette, France.

Merouane Debbah is a professor at Sup�lec, Gif-sur-Yvette, France. He is the holder of the Alcatel-Lucent chair in flexible radio since 2007.

About the Author
Samson received his BSc and Agr�gation degree in Applied Physics from �cole Normale Sup�rieure (Cachan) and his MSc and PhD in Signal Processing from �cole Nationale Sup�rieure des T�l�communications (Paris). Professional experience. He has been working with Motorola Labs for three years (1999, 2000, 2001) and with France T�l�com R&D for two years (2002, 2003). Since 2004, he has joined the CNRS and Sup�lec. Since 2004, he is also Charg� d'Enseignement at �cole Polytechnique. His broad interests lie in the areas of communications, signal processing and information theory with a special emphasis on game theory for wireless communications. Samson Lasaulce is the recipient of the 2007 ACM/ICST International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS) and 2009 International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM) best student paper awards. Elena Veronica Belmega, who is a PhD student under my supervision, was awarded with the 2009 Academy of Sciences - L'Oreal - Unesco award for young women in sciences in France.

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Friday, January 1, 2010

[G584.Ebook] Fee Download Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

Fee Download Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

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Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn



Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

Fee Download Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

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Option Valuation: A First Course in Financial Mathematics (Chapman and Hall/CRC Financial Mathematics Series), by Hugo D. Junghenn

Option Valuation: A First Course in Financial Mathematics provides a straightforward introduction to the mathematics and models used in the valuation of financial derivatives. It examines the principles of option pricing in detail via standard binomial and stochastic calculus models. Developing the requisite mathematical background as needed, the text presents an introduction to probability theory and stochastic calculus suitable for undergraduate students in mathematics, economics, and finance.

The first nine chapters of the book describe option valuation techniques in discrete time, focusing on the binomial model. The author shows how the binomial model offers a practical method for pricing options using relatively elementary mathematical tools. The binomial model also enables a clear, concrete exposition of fundamental principles of finance, such as arbitrage and hedging, without the distraction of complex mathematical constructs. The remaining chapters illustrate the theory in continuous time, with an emphasis on the more mathematically sophisticated Black-Scholes-Merton model.

Largely self-contained, this classroom-tested text offers a sound introduction to applied probability through a mathematical finance perspective. Numerous examples and exercises help students gain expertise with financial calculus methods and increase their general mathematical sophistication. The exercises range from routine applications to spreadsheet projects to the pricing of a variety of complex financial instruments. Hints and solutions to odd-numbered problems are given in an appendix and a full solutions manual is available for qualifying instructors.

  • Sales Rank: #1427222 in Books
  • Published on: 2011-11-23
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.30" h x .80" w x 6.10" l, 1.15 pounds
  • Binding: Hardcover
  • 266 pages

Review

"…a suitable text for an advanced undergraduate or graduate-level course in option valuation via the binomial model and the Black–Scholes–Merton model."
―International Statistical Review, 2013

"The text provides an introduction to classical material of mathematical finance, i.e. the notions of arbitrage, replication, and option pricing in the context of the discrete-time Cox-Ross-Rubinstein and the continuous-time Black-Scholes model, respectively. The book sticks out by not assuming any background in stochastics. All necessary concepts of probability theory, martingales, and It� calculus are provided …"
―Jan Kallsen, Zentralblatt MATH 1247

About the Author

Hugo D. Junghenn is a professor of mathematics at the George Washington University. His research interests include functional analysis and semigroups.

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0 of 1 people found the following review helpful.
Not for me
By Chiu-ying Wong
I bought this book because I wanted to learn about the mathematics behind quantitative finance. I have a CFA and an engineering degree (OK it was a while ago), so I know about some financial equations, but I wanted to learn more. I first bought the book Introduction to Quantitative Finance by Wilmott, but found that hard to follow, because it talked about things like Ito's Lemma, Martingale, Wiener Process and so on, and I have no idea what they are. So I thought this book could be an introduction to the introduction. It turns out, this book is more a book for scholars of pure mathematics to access the world of finance. It is not for non-pure maths people to learn the math basics necessary to understand quantitative finance. It goes through definition, corollary, propositions, theorem and proofs in pure math language.

For example, when it introduced the idea of a self-financing portfolio, it did not bother to explain why, what is it, what is its purpose. To quote the paragraph introducing self financing portfolios, and replacing the funny letters with those I can type with a normal keyboard, it goes like this:"Suppose that the price of a security S is given by a stochastic process S = (Sn) to N from n=0 on a probability space (Omega, Funny F, strange P), where S0 is constant. We may assume that Funny F = Funny F from N to S, where Funny F from n to S is the natural filtration for S. Note that because S0 is constant, funny F from 0 to S is the trivial sigma field {0, Omega}...blah blah blah....."

I wish it had spelt out its target audience in the outline of the book. In the Preface inside the book, it said :"This text is intended as an introduction to the mathematics and models used in the valuation of financial derivatives. It is designed for an audience with a background in standard multivariable calculus. Otherwise, the book is essentially self-contained." I learned multivariable calculus from an applied maths angle, and this book is like being written in an alien language. Not for me.

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