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Adaptive Resonance Theory in Social Media Data Clustering: Roles, Methodologies, and Applications (Advanced Information and Knowledge Processing)
by Lei Meng Ah-Hwee Tan Donald C. Wunsch IISocial media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data:Basic knowledge (data & challenges) on social media analyticsClustering as a fundamental technique for unsupervised knowledge discovery and data miningA class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step practices of developing unsupervised machine learning algorithms for real-world applications in social media domainAdaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction.It presents initiatives on the mathematical demonstration of ART’s learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks.Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you:How to process big streams of multimedia data?How to analyze social networks with heterogeneous data?How to understand a user’s interests by learning from online posts and behaviors?How to create a personalized search engine by automatically indexing and searching multimodal information resources? .
Adaptive Power Quality for Power Management Units using Smart Technologies (Future Generation Information Systems)
by Arti Vaish Pankaj Kumar Goswami Surbhi Bhatia Mokhtar ShouranThis book covers issues associated with smart systems due to the presence of onboard nonlinear components. It discusses the advanced architecture of smart systems for power management units. It explores issues of power management and identifies hazardous signals in the power management units of smart devices. It Presents adaptive artificial intelligence and machine learning-based control strategies. Discusses advanced simulations and data synthesis for various power management issues. Showcases solutions to the uncertainty and reliability issues in power management units. Identifies new power quality challenges in smart devices. Explains hybrid active power filters, shunt hybrid active power filters, and the industrial internet of things in power quality management. This book comprehensively discusses advancements of traditional electrical grids, the benefits of smart grids to customers and stakeholders, properties of smart grids, smart grid architecture, smart grid communication, and smart grid security. It further covers the architecture of advance power management units (PMU) of smart devices, and the identification of harmonic distortions with respect to various sensor-based technology. It will serve as an ideal reference text for senior undergraduate and graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.
Adaptive On- and Off-Earth Environments (Springer Series in Adaptive Environments)
by Henriette Bier Angelo Cervone Advenit MakayaThis volume investigates the challenges and opportunities for designing, manufacturing and operating off-Earth infrastructures in order to establish adaptive human habitats. The adaptive aspects are considered with respect to the development of adequate infrastructures designed to support human activities. Given the limitations in bringing materials from Earth, utilisation of in-situ resources is crucial for establishing and maintaining these infrastructures.Adaptive on-and off-Earth Environments focuses, among other aspects, on the design, production, and operation processes required to build and maintain such off-Earth infrastructures, while heavily relying on In-Situ Resource Utilisation (ISRU). Such design, production, and operation processes integrate cyber-physical approaches developed and tested on Earth. The challenge is to adapt on-Earth approaches to off-Earth applications aiming at technology advancement and ultimately transfer from on- to off-Earth research. Thischallenge is addressed with contributions from various disciplines ranging from power generation to architecture, construction, and materials engineering involving ISRU for manufacturing processes. All chapters, related to these disciplines, are structured with an emphasis on computing and adaptivity of on-Earth technology to off-Earth applications and vice versa to serve society at large.
Adaptive Multimedia Retrieval: 10th International Workshop, AMR 2012, Copenhagen, Denmark, October 24-25, 2012, Revised Selected Papers (Lecture Notes in Computer Science #8382)
by Birger Larsen Andreas Nürnberger Sebastian Stober Marcin DetynieckiThis book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012. The 17 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers cover topics of state of the art contributions, features and classification, location context, language and semantics, music retrieval, and adaption and HCI.
Adaptive Middleware for the Internet of Things: The GAMBAS Approach
by Marcus Handte Pedro José Marrón Gregor Schiele Matoses Manuel SerranoOver the past years, a considerable amount of effort has been devoted, both in industry and academia, towards the development of basic technology as well as innovative applications for the Internet of Things. Adaptive Middleware for the Internet of Things introduces a scalable, interoperable and privacy-preserving approach to realize IoT applications and discusses abstractions and mechanisms at the middleware level that simplify the realization of services that can adapt autonomously to the behavior of their users. Technical topics discussed in the book include:Behavior-driven Autonomous ServicesGAMBAS Middleware ArchitectureGeneric and Efficient Data AcquisitionInteroperable and Scalable Data ProcessingAutomated Privacy PreservationAdaptive Middleware for the Internet of Things summarizes the results of the GAMBAS research project funded by the European Commission under Framework Programme 7. It provides an in-depth description of the middleware system developed by the project consortium. In addition, the book describes several innovative mobility and monitoring applications that have been built, deployed and operated to evaluate the middleware under realistic conditions with a large number of users. Adaptive Middleware for the Internet of Things is ideal for personnel in the computer and communication industries as well as academic staff and research students in computer science interested in the development of systems and applications for the Internet of Things.
Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices
by Chanchal ChatterjeeLearn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use. Authors Chanchal Chatterjee and Vwani P. Roychowdhury begin by introducing a common framework for creating adaptive algorithms, and demonstrating how to use it to address various streaming data issues. Examples range from using matrix functions to solve machine learning and data analysis problems to more critical edge computation problems. They handle time-varying, non-stationary data with minimal compute, memory, latency, and bandwidth. Upon finishing this book, you will have a solid understanding of how to solve adaptive machine learning and data analytics problems and be able to derive new algorithms for your own use cases. You will also come away with solutions to high volume time-varying data with high dimensionality in a low compute, low latency environment. What You Will Learn Apply adaptive algorithms to practical applications and examplesUnderstand the relevant data representation features and computational models for time-varying multi-dimensional dataDerive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real dataSpeed up your algorithms and put them to use on real-world stationary and non-stationary dataMaster the applications of adaptive algorithms on critical edge device computation applications Who This Book Is ForMachine learning engineers, data scientist and architects, software engineers and architects handling edge device computation and data management.
Adaptive Instructional Systems. Design and Evaluation: Third International Conference, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part I (Lecture Notes in Computer Science #12792)
by Jessica Schwarz Robert A. SottilareThis two-volume set LNCS 12792 and 12793 constitutes the refereed proceedings of the Third International Conference on Adaptive Instructional Systems, AIS 2021, held as Part of the 23rd International Conference, HCI International 2021, which took place in July 2021. Due to COVID-19 pandemic the conference was held virtually.The total of 1276 papers and 241 poster papers included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The regular papers of AIS 2021, Part I, are organized in topical sections named: Conceptual Models and Instructional Approaches for AIS; Designing and Developing AIS; Evaluation of AIS; Adaptation Strategies and Methods in AIS.
Adaptive Instructional Systems. Adaptation Strategies and Methods: Third International Conference, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part II (Lecture Notes in Computer Science #12793)
by Robert A. Sottilare Jessica SchwarzThis two-volume set LNCS 12774 and 12775 constitutes the refereed proceedings of the 12th International Conference on Social Computing and Social Media, SCSM 2021, held as part of the 23rd International Conference, HCI International 2021, which took place in July 2021. Due to COVID-19 pandemic the conference was held virtually. The total of 1276 papers and 241 poster papers included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The regular papers of AIS 2021, Part II, focus on Learner Modelling and State Assessment in AIS.
Adaptive Instructional Systems: Second International Conference, AIS 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings (Lecture Notes in Computer Science #12214)
by Jessica Schwarz Robert A. SottilareThis volume constitutes the refereed proceedings of the Second International Conference on Adaptive Instructional Systems, AIS 2020, which was due to be held in July 2020 as part of HCI International 2020 in Copenhagen, Denmark. The conference was held virtually due to the COVID-19 pandemic.A total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings from a total of 6326 submissions. The 41 papers presented in this volume were organized in topical sections as follows: designing and developing adaptive instructional systems; learner modelling and methods of adaptation; evaluating the effectiveness of adaptive instructional systems.Chapter "Exploring Video Engagement in an Intelligent Tutoring System" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Adaptive Instructional Systems: 6th International Conference, AIS 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings (Lecture Notes in Computer Science #14727)
by Jessica Schwarz Robert A. SottilareThis book constitutes the refereed proceedings of 6th International Conference on Adaptive Instructional Systems, AIS 2024, held as part of the 26th International Conference, HCI International 2024, which took place in Washington, DC, USA, during June 29-July 4, 2024. The total of 1271 papers and 309 posters included in the HCII 2024 proceedings was carefully reviewed and selected from 5108 submissions. The HCII-AIS 2024 contributions have been organized in the following topical sections: Designing and developing adaptive instructional systems; adaptive learning experiences; AI in adaptive learning.
Adaptive Instructional Systems: First International Conference, AIS 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings (Lecture Notes in Computer Science #11597)
by Robert A. Sottilare Jessica SchwarzThis book constitutes the refereed proceedings of the First International Conference on Adaptive Instructional Systems, AIS 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 50 papers presented in this volume are organized in topical sections named: Adaptive Instruction Design and Authoring, Interoperability and Standardization in Adaptive Instructional Systems, Instructional Theories in Adaptive Instruction, Learner Assessment and Modelling, AI in Adaptive Instructional Systems, Conversational Tutors.
Adaptive Instructional Systems: 5th International Conference, AIS 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings (Lecture Notes in Computer Science #14044)
by Robert A. Sottilare Jessica SchwarzThis book constitutes the refereed proceedings of the 5th International Conference, AIS 2023, held as part of the 25th International Conference, HCI International 2023, which was held virtually in Copenhagen, Denmark in July 2023.The total of 1578 papers and 396 posters included in the HCII 2023 proceedings was carefully reviewed and selected from 7472 submissions. The AIS 2023 proceeding helps to understand the theory and enhance the state-of-practice for a set of technologies (tools and methods) called adaptive instructional systems (AIS). AIS are defined as artificially intelligent, computer-based systems that guide learning experiences by tailoring instruction and recommendations based on the goals, needs, preferences, and interests of each individual learner or team in the context of domain learning objectives.
Adaptive Instructional Systems: 4th International Conference, AIS 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings (Lecture Notes in Computer Science #13332)
by Robert A. Sottilare Jessica SchwarzThis book constitutes the refereed proceedings of the 4th International Conference on Adaptive Instructional Systems, AIS 2022, held as part of the 23rd International Conference, HCI International 2022, which was held virtually in June/July 2022.The total of 1271 papers and 275 posters included in the HCII 2022 proceedings was carefully reviewed and selected from 5487 submissions. The AIS 2022 proceedings were organized in the following topical sections: Learner Modeling and State Assessment for Adaptive Instructional Decisions; Adaptation Design to Individual Learners and Teams; Design and Development of Adaptive Instructional Systems; Evaluating the Effectiveness of Adaptive Instructional Systems.
Adaptive Image Processing Algorithms for Printing (Signals and Communication Technology)
by Ilia V. Safonov Ilya V. Kurilin Michael N. Rychagov Ekaterina V. TolstayaThis book presents essential algorithms for the image processing pipeline of photo-printers and accompanying software tools, offering an exposition of multiple image enhancement algorithms, smart aspect-ratio changing techniques for borderless printing and approaches for non-standard printing modes. All the techniques described are content-adaptive and operate in an automatic mode thanks to machine learning reasoning or ingenious heuristics. The first part includes algorithms, for example, red-eye correction and compression artefacts reduction, that can be applied in any photo processing application, while the second part focuses specifically on printing devices, e. g. eco-friendly and anaglyph printing. The majority of the techniques presented have a low computational complexity because they were initially designed for integration in system-on-chip. The book reflects the authors' practical experience in algorithm development for industrial R&D.
Adaptive Image Processing: A Computational Intelligence Perspective, Second Edition (Image Processing Series)
by Kim-Hui Yap Ling Guan Stuart William Perry Hau San WongIllustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI) methods and algorithms for adaptive image processing in regularization, edge detection, and early vision. With three new chapters and updated information throughout, the new edition of this popular reference includes substantial new material that focuses on applications of advanced CI techniques in image processing applications. It introduces new concepts and frameworks that demonstrate how neural networks, support vector machines, fuzzy logic, and evolutionary algorithms can be used to address new challenges in image processing, including low-level image processing, visual content analysis, feature extraction, and pattern recognition. Emphasizing developments in state-of-the-art CI techniques, such as content-based image retrieval, this book continues to provide educators, students, researchers, engineers, and technical managers in visual information processing with the up-to-date understanding required to address contemporary challenges in image content processing and analysis.
Adaptive Filtering Under Minimum Mean p-Power Error Criterion
by Badong Chen Wentao MaAdaptive filtering still receives attention in engineering as the use of the adaptive filter provides improved performance over the use of a fixed filter under the time-varying and unknown statistics environments. This application evolved communications, signal processing, seismology, mechanical design, and control engineering. The most popular optimization criterion in adaptive filtering is the well-known minimum mean square error (MMSE) criterion, which is, however, only optimal when the signals involved are Gaussian-distributed. Therefore, many "optimal solutions" under MMSE are not optimal. As an extension of the traditional MMSE, the minimum mean p-power error (MMPE) criterion has shown superior performance in many applications of adaptive filtering. This book aims to provide a comprehensive introduction of the MMPE and related adaptive filtering algorithms, which will become an important reference for researchers and practitioners in this application area. The book is geared to senior undergraduates with a basic understanding of linear algebra and statistics, graduate students, or practitioners with experience in adaptive signal processing.Key Features: Provides a systematic description of the MMPE criterion. Many adaptive filtering algorithms under MMPE, including linear and nonlinear filters, will be introduced. Extensive illustrative examples are included to demonstrate the results.
Adaptive Filtering Primer with MATLAB
by Alexander D. Poularikas Zayed M. Ramadan<p>Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fundamentals of this field was necessary. The material and the principles presented in this book are easily accessible to engineers, scientists, and students who would like to learn the fundamentals of this field and have a background at the bachelor level. <p>Adaptive Filtering Primer with MATLAB clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage. <p>With applications across a wide range of areas, including radar, communications, control, medical instrumentation, and seismology, Adaptive Filtering Primer with MATLAB is an ideal companion for quick reference and a perfect, concise introduction to the field.</p>
Adaptive Educational Technologies for Literacy Instruction
by Scott A. Crossley Danielle S. McNamaraWhile current educational technologies have the potential to fundamentally enhance literacy education, many of these tools remain unknown to or unused by today’s practitioners due to a lack of access and support. Adaptive Educational Technologies for Literacy Instruction presents actionable information to educators, administrators, and researchers about available educational technologies that provide adaptive, personalized literacy instruction to students of all ages. These accessible, comprehensive chapters, written by leading researchers who have developed systems and strategies for classrooms, introduce effective technologies for reading comprehension and writing skills.
Adaptive Dynamic Programming with Applications in Optimal Control (Advances in Industrial Control)
by Ding Wang Derong Liu Qinglai Wei Xiong Yang Hongliang LiThis book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP approach which is then extended to other branches of control theory including decentralized control, robust and guaranteed cost control, and game theory. In the last part of the book the real-world significance of ADP theory is presented, focusing on three application examples developed from the authors' work: * renewable energy scheduling for smart power grids; * coal gasification processes; and * water-gas shift reactions. Researchers studying intelligent control methods and practitioners looking to apply them in the chemical-process and power-supply industries will find much to interest them in this thorough treatment of an advanced approach to control.
Adaptive Dynamic Programming for Control: Algorithms and Stability (Communications and Control Engineering)
by Yanhong Luo Huaguang Zhang Ding Wang Derong LiuThere are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: * infinite-horizon control for which the difficulty of solving partial differential Hamilton-Jacobi-Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; * finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; * nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: * establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; * demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and * shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.
Adaptive Dynamic Programming: Single and Multiple Controllers (Studies in Systems, Decision and Control #166)
by Ruizhuo Song Qinglai Wei Qing LiThis book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.
Adaptive Digital Filters
by Zoran Banjac Milan Milosavljević Branko Kovačević"Adaptive Digital Filters" presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in mastering this important field.
Adaptive Digital Circuits for Power-Performance Range beyond Wide Voltage Scaling: From the Clock Path to the Data Path
by Massimo Alioto Saurabh Jain Longyang LinThis book offers the first comprehensive coverage of digital design techniques to expand the power-performance tradeoff well beyond that allowed by conventional wide voltage scaling. Compared to conventional fixed designs, the approach described in this book makes digital circuits more versatile and adaptive, allowing simultaneous optimization at both ends of the power-performance spectrum. Drop-in solutions for fully automated and low-effort design based on commercial CAD tools are discussed extensively for processors, accelerators and on-chip memories, and are applicable to prominent applications (e.g., IoT, AI, wearables, biomedical). Through the higher power-performance versatility techniques described in this book, readers are enabled to reduce the design effort through reuse of the same digital design instance, across a wide range of applications. All concepts the authors discuss are demonstrated by dedicated testchip designs and experimental results. To make the results immediately usable by the reader, all the scripts necessary to create automated design flows based on commercial tools are provided and explained.
Adaptive Control of Bio-Inspired Manufacturing Systems (Research on Intelligent Manufacturing)
by Dunbing Tang Kun Zheng Wenbin GuThis book introduces state-of-the-art models and methods based on the neuroendocrine-immune-inspired approaches in the field of manufacturing control systems. It develops various bio-inspired intelligent approaches for multiple applications in order to efficiently generate production plans and control solutions and agilely deal with the frequent unexpected disturbances at the shop floor level. It also provides an introduction to bio-inspired manufacturing systems with intelligent control structures and the latest technologies. Further, the book describes recent advances in the bio-inspired methodology for a high-level adaptability in manufacturing systems, including the bio-inspired control architecture and the implementation of intelligent and adaptive control approaches based on neuroendocrine-immune mechanisms and hormone-regulation principles. It offers a valuable resource for graduate students, researchers and engineers in the fields of production management, manufacturing system control and related areas.
Adaptive Biometric Systems: Recent Advances and Challenges (Advances in Computer Vision and Pattern Recognition)
by Ajita Rattani Fabio Roli Eric GrangerThis interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system.