Adaptive Filtering And Change Detection
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Adaptive Filtering And Change Detection
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Author : Fredrik Gustafsson
language : en
Publisher: John Wiley & Sons
Release Date : 2000-10-03
Adaptive Filtering And Change Detection written by Fredrik Gustafsson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-10-03 with Science categories.
Adaptive filtering is a branch of digital signal processing which enables the selective enhancement of desired elements of a signal and the reduction of undesired elements. Change detection is another kind of adaptive filtering for non-stationary signals, and is the basic tool in fault detection and diagnosis. This text takes the unique approach that change detection is a natural extension of adaptive filtering, and the broad coverage encompasses both the mathematical tools needed for adaptive filtering and change detection and the applications of the technology. Real engineering applications covered include aircraft, automotive, communication systems, signal processing and automatic control problems. The unique integration of both theory and practical applications makes this book a valuable resource combining information otherwise only available in separate sources Comprehensive coverage includes many examples and case studies to illustrate the ideas and show what can be achieved Uniquely integrates applications to airborne, automotive and communications systems with the essential mathematical tools Accompanying Matlab toolbox available on the web illustrating the main ideas and enabling the reader to do simulations using all the figures and numerical examples featured This text would prove to be an essential reference for postgraduates and researchers studying digital signal processing as well as practising digital signal processing engineers.
Multitemporal Remote Sensing
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Author : Yifang Ban
language : en
Publisher: Springer
Release Date : 2016-12-01
Multitemporal Remote Sensing written by Yifang Ban and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-01 with Technology & Engineering categories.
Written by world renowned scientists, this book provides an excellent overview of a wide array of methods and techniques for the processing and analysis of multitemporal remotely sensed images. These methods and techniques include change detection, multitemporal data fusion, coarse-resolution time series processing, and interferometric SAR multitemporal processing, among others. A broad range of multitemporal datasets are used in their methodology demonstrations and application examples, including multispectral, hyperspectral, SAR and passive microwave data. This book features a variety of application examples covering both land and aquatic environments. Land applications include urban, agriculture, habitat disturbance, vegetation dynamics, soil moisture, land surface albedo, land surface temperature, glacier and disaster recovery. Aquatic applications include monitoring water quality, water surface areas and water fluctuation in wetland areas, spatial distribution patterns and temporal fluctuation trends of global land surface water, as well as evaluation of water quality in several coastal and marine environments. This book will help scientists, practitioners, students gain a greater understanding of how multitemporal remote sensing could be effectively used to monitor our changing planet at local, regional, and global scales.
Image Analysis Classification And Change Detection In Remote Sensing
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Author : Morton J. Canty
language : en
Publisher: CRC Press
Release Date : 2014-06-06
Image Analysis Classification And Change Detection In Remote Sensing written by Morton J. Canty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-06 with Mathematics categories.
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Networked Filtering And Fusion In Wireless Sensor Networks
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Author : Magdi S. Mahmoud
language : en
Publisher: CRC Press
Release Date : 2014-12-20
Networked Filtering And Fusion In Wireless Sensor Networks written by Magdi S. Mahmoud and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-20 with Computers categories.
By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. Networked Filtering and Fusion in Wireless Sensor Networks introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems.T
Signal And Image Processing For Remote Sensing
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Author : C.H. Chen
language : en
Publisher: CRC Press
Release Date : 2006-10-09
Signal And Image Processing For Remote Sensing written by C.H. Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-09 with Technology & Engineering categories.
Most data from satellites are in image form, thus most books in the remote sensing field deal exclusively with image processing. However, signal processing can contribute significantly in extracting information from the remotely sensed waveforms or time series data. Pioneering the combination of the two processes, Signal and Image Processing for Re
Geospatial Technologies For Resources Planning And Management
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Author : Chandra Shekhar Jha
language : en
Publisher: Springer Nature
Release Date : 2022-05-24
Geospatial Technologies For Resources Planning And Management written by Chandra Shekhar Jha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-24 with Science categories.
This book focuses on the application of geospatial technologies for resource planning and management for the key natural resources, e.g. water, agriculture and forest as well as the decision support system (DSS) for infrastructure development. We have seen in the past four decades that the growing complexities of sustainable management of natural resources management have been very challenging. The book has been written to leverage the current geospatial technologies that integrate the remotely sensed data available from various platforms, the precise locational data providing geospatial intelligence, and the advanced integration tools of Geographical Information Systems (GIS). Geospatial technologies have been used for water resources management employing geomorphological characteristics, analysis of river migration pattern, understanding the large-scale hydrological process, wet land classification and monitoring, analysis of glacial lake outburst flood (GLOF), assessment of environmental flow and soil erosion studies, water quality modelling and assessment and rejuvenation of paleochannels through groundwater recharge. Geospatial technologies have been applied for crop classification and mapping, soil moisture determination using RISAT-1 C-band and PALSAR-2 L-band sensors, inventory of horticulture plantations, management of citrus orchards, crop yield forecasting, rice yield estimation, estimation of evapotranspiration and its evaluation against lysimeter and satellite-based evapotranspiration product for India to address the various issues of the agricultural system management. Geospatial technologies have been used for generation of digital elevation model, urban dynamics assessment, mobile GIS application at grass root level planning, cadastral level developmental planning and e-governance applications, system dynamics for sustainable development, micro-level water resources planning, site suitability for sewage treatment plant, traffic density assessment, geographical indications of India, archaeological applications and disasters interventions to elaborate various issues of DSS for infrastructure development and management. Geospatial technologies have been employed for the generation and reconciliation of the notified forest land boundaries, and also the land cover changes analysis within notified forest areas, forest resource assessment, management and monitoring and wildlife conservation and management. This book aims to present high-quality technical case studies representing the recent developments in the “application of geospatial technologies for resource planning and management”. The editors hope that this book will serve as a valuable resource for scientists and researchers to plan and manage land and water resources sustainably.
Machine Learning Methods For Behaviour Analysis And Anomaly Detection In Video
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Author : Olga Isupova
language : en
Publisher: Springer
Release Date : 2018-02-24
Machine Learning Methods For Behaviour Analysis And Anomaly Detection In Video written by Olga Isupova and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-24 with Technology & Engineering categories.
This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed. The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.
Advances In Industrial Engineering And Operations Research
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Author : Alan H.S. Chan
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-03
Advances In Industrial Engineering And Operations Research written by Alan H.S. Chan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-03 with Business & Economics categories.
This volume contains contributions from prominent researchers who participated in the 2007 IAENG International Conference on Operations Research. It presents theories and applications of modern industrial engineering and operations research to meet the needs of rapidly developing fields. The book reflects the tremendous advances in communication systems and electrical engineering and also serves as an excellent reference work for researchers and graduate students.
Frontiers Of Intelligent Control And Information Processing
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Author : Derong Liu
language : en
Publisher: World Scientific
Release Date : 2014-08-13
Frontiers Of Intelligent Control And Information Processing written by Derong Liu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-13 with Technology & Engineering categories.
The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity.As researches in intelligent control and information processing are taking on ever more complex problems, the control system as a nuclear to coordinate the activity within a system increasingly need to be equipped with the capability to analyze, and reason so as to make decision. This requires the support of cognitive components, and communication protocol to synchronize events within the system to operate in unison.In this review volume, we invited several well-known experts and active researchers from adaptive/approximate dynamic programming, reinforcement learning, machine learning, neural optimal control, networked systems, and cyber-physical systems, online concept drift detection, pattern recognition, to contribute their most recent achievements into the development of intelligent control systems, to share with the readers, how these inclusions helps to enhance the cognitive capability of future control systems in handling complex problems.This review volume encapsulates the state-of-art pioneering works in the development of intelligent control systems. Proposition and evocations of each solution is backed up with evidences from applications, could be used as references for the consideration of decision support and communication components required for today intelligent control systems.
Towards Advanced Data Analysis By Combining Soft Computing And Statistics
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Author : Christian Borgelt
language : en
Publisher: Springer
Release Date : 2012-08-29
Towards Advanced Data Analysis By Combining Soft Computing And Statistics written by Christian Borgelt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-29 with Technology & Engineering categories.
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.