Items related to A Matching Theorem for Locally Stationary Random Processes...
Synopsis
Uncover how to model changing signals with stable behavior inside short intervals.
This book shows how to describe locally stationary random processes and how to tailor their power and memory to fit real-world data.
Grounded in second-order analysis, the material explains what makes a process locally stationary and how to quantify its instantaneous power and memory. It introduces a practical “matching theorem” that lets you align a process’s autocorrelation with a chosen power schedule through smoothing and aperture-limiting techniques. The approach blends intuition with rigorous results, offering tools you can apply to time-varying signals and noise models.Key ideas are presented with a focus on accessibility and applicability: how to construct locally stationary covariances, how harmonic analysis helps reveal structure, and how Gaussian smoothing can bridge desired properties. The text also discusses the limits of these models and how they relate to globally stationary cases.
- Understanding what makes a process locally stationary and how to identify its power schedule
- The matching theorem and how smoothing or limiting the autocorrelation helps align components
- How Gaussian kernels act as smoothers in constructing viable models
- Connections between time-domain descriptions and their spectral (Fourier) counterparts
Ideal for readers of stochastic processes and time-series theory who want a practical, theory-backed framework for modeling non-stationary signals.
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A Matching Theorem for Locally Stationary Random Processes (Classic Reprint)
Print on DemandSeller: Forgotten Books, London, United Kingdom
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Paperback. Condition: New. Print on Demand. This book delves into the study of locally stationary random processes, introducing a theory that enables the conversion of non-negative functions and continuous correlation functions into integral components of a locally stationary process. The author sheds light on how these processes can be smoothed and limited in aperture to match each other, thereby expanding the harmonic analysis techniques conventionally used for globally stationary processes. The book systematically explores the conceptual foundation of locally stationary processes, providing a cohesive framework for understanding their behavior and properties. Through rigorous mathematical analysis and practical examples, the author uncovers the significance of these processes in various scientific disciplines, such as noise analysis and dielectric modeling. This book is a valuable resource for researchers, scientists, and engineers seeking a deeper understanding of random processes and their applications. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781333041113_0
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A Matching Theorem for Locally Stationary Random Processes (Classic Reprint)
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781333041113
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A Matching Theorem for Locally Stationary Random Processes (Classic Reprint)
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781333041113
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