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Small Universal Cellular Automata In Hyperbolic Spaces

RRP $27.99

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Hyperbolic geometry is an essential part of theoretical astrophysics and cosmology. Besides specialists of these domains, many specialists of new domains start to show a growing interest
both to hyperbolic geometry and to cellular automata. This is especially the case in biology and computer science.

This book gives the reader a deep and efficient introduction to an algorithmic approach to hyperbolic geometry. It focuses the attention on the possibilities to obtain in this frame the power of computing everything a computer can compute, that is to say: universality.

The minimal ways to get universality are investigated in a large family of tilings of the hyperbolic plane. In several cases the best results are obtained.In all cases, the results are close to the theoretical best values. This gives rise to fantastic illustrations: the results are jewels in all meanings of the word.

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Maurice MARGENSTERN is professor emeritus at the University of Lorraine, he is a member of LITA, the research unit of computer science in the campus of Metz of this university. Professor Margenstern is amongst top world experts in theory of computation, mathematical machines and geometry. He is a pioneer
in cellular automata in hyperbolic spaces.


Small Towns And Villages In Bavaria

RRP $289.99

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At the center of this investigation is the great modernization effort of a West German state, Bavaria, in the 1970s and 1980s, by means of a reform of the smaller units of local government. The reforms were meant to abolish all autonomous local governments serving populations of fewer than 3,000, thereby reducing the number of local governments in Bavaria from more than 7,000 to less than 2,000. Based on interviews, surveys, and statistical research, this study chronicles fifteen communities and their challenges, developments, and social changes from post-1945 up to the present. While this book explores the decline of the iconic village community, it also reveals the survival of medieval towns in a contemporary world, and despite the modern desire for comprehensive and well-integrated services, there remains a seemingly perennial appeal of small town and village life.


Identification Of Dynamical Systems With Small Noise

RRP $119.00

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Small noise is a good noise. In this work, we are interested in the problems of estimation theory concerned with observations of the diffusion-type process Xo = Xo, 0 ~ t ~ T, (0. 1) where W is a standard Wiener process and St(') is some nonanticipative smooth t function. By the observations X = {X , 0 ~ t ~ T} of this process, we will solve some t of the problems of identification, both parametric and nonparametric. If the trend S(-) is known up to the value of some finite-dimensional parameter St(X) = St((}, X), where (} E e c Rd , then we have a parametric case. The nonparametric problems arise if we know only the degree of smoothness of the function St(X), 0 ~ t ~ T with respect to time t. It is supposed that the diffusion coefficient c is always known. In the parametric case, we describe the asymptotical properties of maximum likelihood (MLE), Bayes (BE) and minimum distance (MDE) estimators as c --+ 0 and in the nonparametric situation, we investigate some kernel-type estimators of unknown functions (say, StO,O ~ t ~ T). The asymptotic in such problems of estimation for this scheme of observations was usually considered as T --+ 00 , because this limit is a direct analog to the traditional limit (n --+ 00) in the classical mathematical statistics of i. i. d. observations. The limit c --+ 0 in (0. 1) is interesting for the following reasons.


A Beginner's Guide To Investing

RRP $16.99

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Whether you're a complete investing novice or just confused about all the contradictory advice out there, A Beginner's Guide to Investing is an accessible guide to growing your money the smart and easy way. Throw away the get-rich quick schemes that never work and turn off the financial news and it's constant noise. Whether your dream is protecting your assets in a turbulent market or growing your wealth so that you can retire in style, this book is the blueprint. You can be a successful investor - really. Join Ivy Bytes, an innovative start-up dedicated to creating accessible content on crucial issues, and Alex Frey, a lifelong investor and Harvard MBA, as they show you: - How you can realistically expect to double your money every 7-10 years - Why most investors achieve stunningly poor returns on their money - and how to avoid turning into one of them - How to choose an investment account that you can keep for the rest of your life - How to out-perform the vast majority of professional investors while taking less risk - How to quickly create a portfolio of diversified ETFs (exchange traded funds) - How to put in as few as three to five hours every year on your investing - and still beat 80% of investors - Why you may not be properly diversified in holding the most popular index mutual funds - How endowments like Yale university have consistently beaten the overall stock market - and what you can learn from them - Why the vast majority of mutual funds fail to live up to their promise - Why your financial adviser and mutual fund manager might be getting more rich than you off of your investments - What the terms "beta" and "alpha" mean - and why understanding them is critical to retiring rich - How to maximize your tax savings by using a 401(k) and IRA - When and how to re-balance your portfolio - How to have the confidence to manage your money for life - And more. About the Authors Alex Frey has been engrossed in the investing world since the age of 16. He has served previously as a research analyst for a major mutual fund company. Alex has successfully passed all three Chartered Financial Analyst examinations, and has an MBA from the Harvard Business School. He lives in San Francisco, CA. When he is not writing, he enjoys reading, investing, and doing just about anything outdoors. Ivy Bytes is an innovative start-up building authoritative, yet accessible guides to subjects in the fields of politics, current events, economics, and finance. Ivy Bytes books are thoroughly researched and extensively fact-checked, so that you can be sure you are getting the latest in mainstream thought - not misguided conspiracy theories or reckless self-promotion.


Identification Of Dynamical Systems With Small Noise

RRP $629.99

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This volume studies parametric and nonparametric estimation through the observation of diffusion-type processes. The properties of maximum likelihood, Bayes, and minimum distance estimators are considered in the context of the asymptotics of low noise. It is shown that, under certain conditions relating to regularity, these estimators are consistent and asymptotically normal. Their properties in nonregular cases are also discussed. Here, nonregularity means the absence of derivatives with respect to parameters, random initial value, incorrectly specified observations, nonidentifiable models, etc. The book has seven chapters. The first presents some auxiliary results needed in the subsequent work. Chapter 2 is devoted to the asymptotic properties of estimators in standard and nonstandard situations. Chapter 3 considers expansions of the maximum likelihood estimator and the distribution function. Chapters 4 and 5 cover nonparametric estimation and the disorder problem. Chapter 6 discusses problems of parameter estimator for linear and nonlinear partially observed models. The final chapter studies the properties of a wide range of minimum distance estimators. The book concludes with a remarks section, references and index. The volume will be of interest to statisticians, researchers in probability theory and stochastic processes, systems theory and communication theory.



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