Найти книгу: "Maga hasti!"

Kui Olivia Brookes politseisse helistab, et teatada oma abikaasaja laste kadumisest, on tal pohjust karta halvimat – see ei ole esimenetragoodia tema elus. Kaks aastat hiljem kutsutakse politseikomissar TomDouglas taas selle perekonna majja, seekord on kadunud Olivia ise. Ja siisleitakse verd. Politsei tahab avaldada tagaotsimiskuulutuse, kuid koikperepildid on albumitest, telefonidest ja arvutitest on hoolikalt kustutatud.Kas minevik on Olivia katte saanud? Maga hasti … kui saad. Sa ei tea, kessind jalgida voib.

Louise Hay on neile kusimustele vastanud juba enam kui 30 aasta jooksul oma imetabaste enesetervendamistehnikatega. Miljonid inimesed on enda ravimiseks valja arendanud isikliku positiivse motlemise meetodi, kasutades tema afirmatsioone, kuid alles nuud oleme voimelised aru saama nende tehnikate taga seisvast teadusest. Raamatus “Koik on hasti” vaatleb meditsiinidoktor ja selgeltnagija Mona Lisa Schulz afirmatsioone teaduslikke meetodeid kasutades, viies tervendamise jargmisele tasandile. Selle raamatu abil opid sa… •…haalestama enda intuitsiooni, et kuulda keha haalt; •…uusi imelisi afirmatsioone ning seda, kuidas neid sinu eriparaste terviseprobleemide puhul rakendada; •…ara tundma emotsionaalseid blokeeringuid ning neid eemaldama, et tuhistada nende moju sinu kehale; •…kombineerima parimat, mida laane meditsiinil on pakkuda, alternatiivsete ravimeetoditega; •…inspireerivaid lugusid haigusega silmitsi seisnud inimestest ning sellest, millised emotsioone ja fuusist puudutavad ettekirjutused neil paraneda aitasid. Peagi teed sa tutvust afirmatsioonide, enda intuitsiooni ja arstiteaduse uusimate avastustega, mis annavad sulle optimaalse tervise ja heaolu ning kindla teadmise, mis koondub Louise’i sonadesse: “Koik on hasti.”

Mathematical finance requires the use of advanced mathematical techniques drawn from the theory of probability, stochastic processes and stochastic differential equations. These areas are generally introduced and developed at an abstract level, making it problematic when applying these techniques to practical issues in finance. Problems and Solutions in Mathematical Finance Volume I: Stochastic Calculus is the first of a four-volume set of books focusing on problems and solutions in mathematical finance. This volume introduces the reader to the basic stochastic calculus concepts required for the study of this important subject, providing a large number of worked examples which enable the reader to build the necessary foundation for more practical orientated problems in the later volumes. Through this application and by working through the numerous examples, the reader will properly understand and appreciate the fundamentals that underpin mathematical finance. Written mainly for students, industry practitioners and those involved in teaching in this field of study, Stochastic Calculus provides a valuable reference book to complement one’s further understanding of mathematical finance.

One of the first books to provide in-depth and systematic application of finite element methods to the field of stochastic structural dynamics The parallel developments of the Finite Element Methods in the 1950’s and the engineering applications of stochastic processes in the 1940’s provided a combined numerical analysis tool for the studies of dynamics of structures and structural systems under random loadings. In the open literature, there are books on statistical dynamics of structures and books on structural dynamics with chapters dealing with random response analysis. However, a systematic treatment of stochastic structural dynamics applying the finite element methods seems to be lacking. Aimed at advanced and specialist levels, the author presents and illustrates analytical and direct integration methods for analyzing the statistics of the response of structures to stochastic loads. The analysis methods are based on structural models represented via the Finite Element Method. In addition to linear problems the text also addresses nonlinear problems and non-stationary random excitation with systems having large spatially stochastic property variations. A systematic treatment of stochastic structural dynamics applying the finite element methods Highly illustrated throughout and aimed at advanced and specialist levels, it focuses on computational aspects instead of theory Emphasizes results mainly in the time domain with limited contents in the time-frequency domain Presents and illustrates direction integration methods for analyzing the statistics of the response of linear and nonlinear structures to stochastic loads Under Author Information – one change of word to existing text: He is a Fellow of the American Society of Mechanical Engineers (ASME)........

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naive stochastic integration, rather than on abstract theories of measure and stochastic processes. The proofs are rather simple for practitioners and, at the same time, rather rigorous for mathematicians. Detailed application examples in natural sciences and finance are presented. Much attention is paid to simulation diffusion processes. The topics covered include Brownian motion; motivation of stochastic models with Brownian motion; Ito and Stratonovich stochastic integrals, Ito’s formula; stochastic differential equations (SDEs); solutions of SDEs as Markov processes; application examples in physical sciences and finance; simulation of solutions of SDEs (strong and weak approximations). Exercises with hints and/or solutions are also provided.

A ground-breaking and practical treatment of probability and stochastic processes A Modern Theory of Random Variation is a new and radical re-formulation of the mathematical underpinnings of subjects as diverse as investment, communication engineering, and quantum mechanics. Setting aside the classical theory of probability measure spaces, the book utilizes a mathematically rigorous version of the theory of random variation that bases itself exclusively on finitely additive probability distribution functions. In place of twentieth century Lebesgue integration and measure theory, the author uses the simpler concept of Riemann sums, and the non-absolute Riemann-type integration of Henstock. Readers are supplied with an accessible approach to standard elements of probability theory such as the central limmit theorem and Brownian motion as well as remarkable, new results on Feynman diagrams and stochastic integrals. Throughout the book, detailed numerical demonstrations accompany the discussions of abstract mathematical theory, from the simplest elements of the subject to the most complex. In addition, an array of numerical examples and vivid illustrations showcase how the presented methods and applications can be undertaken at various levels of complexity. A Modern Theory of Random Variation is a suitable book for courses on mathematical analysis, probability theory, and mathematical finance at the upper-undergraduate and graduate levels. The book is also an indispensible resource for researchers and practitioners who are seeking new concepts, techniques and methodologies in data analysis, numerical calculation, and financial asset valuation. Patrick Muldowney, PhD, served as lecturer at the Magee Business School of the UNiversity of Ulster for over twenty years. Dr. Muldowney has published extensively in his areas of research, including integration theory, financial mathematics, and random variation.