### An Introduction to Probability and Stochastic Processes

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Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes,

**Gaussian**and Markov processes, and stochastic differential equations. 1973 edition.Category: Mathematics. ISBN: 9780486490991

### Elementary Theory of Numbers

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Superb introduction to Euclidean algorithm and its consequences, congruences, continued fractions, powers of an integer modulo m,

**Gaussian**integers, Diophantine equations, more. Problems, with answers. Bibliography.Category: Mathematics. ISBN: 9780486663487

### Statistical Inference for Discrete Time Stochastic Processes

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This book offers an overview of statistical inference in stationary, discrete time stochastic processes. It reviews results in the last fifteen years, particularly on non-

**Gaussian**sequences and semi-parametric and non-parametric analysisCategory: Mathematics. ISBN: 9788132207627

### Upper and Lower Bounds for Stochastic Processes

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In addition to its central focus on generic chaining, which allows for optimal bounds in

**Gaussian**and Bernoulli processes, this volume on modern stochastic methods includes key applications and a variety of complete solutions to a number of classical problems.Category: Mathematics. ISBN: 9783642540745

### The Uncertainty in Physical Measurements

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An introduction to the treatment of uncertainty in a phenomenological way, based on examples taken from laboratory experience and distinguishing the causes of uncertainty (there are more than just random errors and

**Gaussian**distributions to consider).Category: Technology. ISBN: 9780387786490

### Measurement Uncertainties in Science and Technology

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This book recasts classical

**Gaussian**error calculus from scratch. The new edition thoroughly restructures and systematizes the text and offers numerous numerical examples, showing how tounderstand uncertainties, to localize the true values of measured values.Category: Science. ISBN: 9783319048871

### Gradually-varied Flow Profiles in Open Channels

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This book shows how to solve GVF profiles using direct integration and

**Gaussian**hypergeometric function. Lays groundwork for computing at one sweep the GVF profiles in a series of sustaining and adverse channels, which may have horizontal slopes between them.Category: Technology. ISBN: 9783642352416

### State-Space Models

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This book explores developments in state-space models and their applications in economics and finance. Coverage includes nonlinear and non-

**Gaussian**time series models, regime-switching and hidden Markov models, and continuous- or discrete-time state processes.Category: Business. ISBN: 9781461477884

### Simulation of Stochastic Processes with Given Accuracy and Reliability

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Simulation has now become an integral part of research and development across many fields of study. Despite the large amounts of literature in the field of simulation and modeling, one recurring problem is the issue of accuracy and confidence level of constructed models. By outlining the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and reliability in functional spaces. The authors explore analysis of the theory of Sub-

**Gaussian**(including**Gaussian**one) and Square**Gaussian**random variables and processes and Cox processes. Methods of simulation of stochastic processes and fields with given accuracy and reliability in some Banach spaces are also considered. Provides an analysis of the theory of Sub-**Gaussian**(including**Gaussian**one) and Square**Gaussian**random variables and processes Contains information on the study of the issue of accuracy and confidence level of constructed models not found in other books on the topic Provides methods and tools in measuring accuracy and reliability in functional spacesCategory: Mathematics. ISBN: 9781785482175

### Bayesian Estimation and Tracking

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A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-

**Gaussian**systems is short on practical methodology, while**Gaussian**methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by**Gaussian**and non-**Gaussian**noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for**Gaussian**-weighted integrals and particle filters for non-**Gaussian**cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.Category: Technology. ISBN: 9780470621707