Tag: Filtering

December 21, 2024

Principles of Nonlinear Filtering Theory

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Free Download Principles of Nonlinear Filtering Theory
English | 2024 | ISBN: 3031776836 | 487 Pages | PDF EPUB (True) | 46 MB
This text presents a comprehensive and unified treatment of nonlinear filtering theory, with a strong emphasis on its mathematical underpinnings. It is tailored to meet the needs of a diverse readership, including mathematically inclined engineers and scientists at both graduate and post-graduate levels. What sets this book apart from other treatments of the topic is twofold. Firstly, it offers a complete treatment of filtering theory, providing readers with a thorough understanding of the subject. Secondly, it introduces updated methodologies and applications that are crucial in today’s landscape. These include finite-dimensional filters, the Yau-Yau algorithm, direct methods, and the integration of deep learning with filtering problems. The book will be an invaluable resource for researchers and practitioners for years to come.

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December 10, 2024

Energy-Filtering Transmission Electron Microscopy

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Free Download Energy-Filtering Transmission Electron Microscopy By Ludwig Reimer (auth.), Professor Dr. Ludwig Reimer (eds.)
1995 | 425 Pages | ISBN: 3662140551 | PDF | 11 MB
Energy-Filtering Transmission Electron Microscopy (EFTEM) presents a summary of the electron optics, the electron-specimen interactions, and the operation and contrast modes of this new field of analytical electron microscopy. The electron optics of filter lenses and the progress in the correction of aberrations are discussed in detail. An evaluation of our present knowledge of plasmon losses and inner-shell ionisations is of increasing interest for a quantitative application of EFTEM in materials and life sciences. This can be realized not only by filtering the elastically scattered electrons but mainly by imaging and analyzing with inelastically scattered electrons at different energy losses up to 2000 eV. The strength of EFTEM is the combination of the modes of electron energy-loss spectroscopy (EELS), Electron Spectroscopic Imaging (ESI) and Diffraction (ESD) and of energy filtering Reflection Electron Microscopy (REM) in one instrument.

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November 24, 2024

Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment

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Free Download Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment
English | 2025 | ISBN: 1032555505 | 283 Pages | EPUB | 8 MB
This book presents the up-to-date research developments and novel methodologies on multi-sensor filtering fusion (MSFF) for a class of complex systems subject to censored data under a constrained network environment. The contents of this book are divided into two parts covering centralized and distributed MSFF design methodologies. The work provides a framework of optimal centralized/distributed filter design and stability and performance analysis for the considered systems along with designed filters. Simulations presented in this book are implemented using MATLAB.

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October 1, 2024

Kalman Filtering Under Information Theoretic Criteria

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Free Download Kalman Filtering Under Information Theoretic Criteria by Badong Chen, Lujuan Dang, Nanning Zheng
English | August 19, 2023 | ISBN: 3031337638 | 309 pages | MOBI | 63 Mb
This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.

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