Advances In Independent Component Analysis And Learning Machines

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Advances in Independent Component Analysis and Learning Machines

Author : Ella Bingham
Publisher : Academic Press
ISBN 13 : 0128028076
Total Pages : 329 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Advances in Independent Component Analysis and Learning Machines by : Ella Bingham

Download or read book Advances in Independent Component Analysis and Learning Machines written by Ella Bingham and published by Academic Press. This book was released on 2015-05-14 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: - A unifying probabilistic model for PCA and ICA - Optimization methods for matrix decompositions - Insights into the FastICA algorithm - Unsupervised deep learning - Machine vision and image retrieval - A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning - A diverse set of application fields, ranging from machine vision to science policy data - Contributions from leading researchers in the field

Independent Component Analysis

Author : Aapo Hyvärinen
Publisher : John Wiley & Sons
ISBN 13 : 0471464198
Total Pages : 505 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Independent Component Analysis by : Aapo Hyvärinen

Download or read book Independent Component Analysis written by Aapo Hyvärinen and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Recent Advances in Big Data and Deep Learning

Author : Luca Oneto
Publisher : Springer
ISBN 13 : 3030168417
Total Pages : 402 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Recent Advances in Big Data and Deep Learning by : Luca Oneto

Download or read book Recent Advances in Big Data and Deep Learning written by Luca Oneto and published by Springer. This book was released on 2019-04-02 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

Independent Component Analysis

Author : Stephen Roberts
Publisher : Cambridge University Press
ISBN 13 : 9780521792981
Total Pages : 358 pages
Book Rating : 4.7/5 (929 download)

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Book Synopsis Independent Component Analysis by : Stephen Roberts

Download or read book Independent Component Analysis written by Stephen Roberts and published by Cambridge University Press. This book was released on 2001-03 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models. ICA provides a better decomposition than other well-known models such as principal component analysis. This self-contained book contains a structured series of edited papers by leading researchers in the field, including an extensive introduction to ICA. The major theoretical bases are reviewed from a modern perspective, current developments are surveyed and many case studies of applications are described in detail. The latter include biomedical examples, signal and image denoising and mobile communications. ICA is discussed in the framework of general linear models, but also in comparison with other paradigms such as neural network and graphical modelling methods. The book is ideal for researchers and graduate students in the field.

Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning

Author : ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.)
Publisher : Springer Nature
ISBN 13 : 3031539958
Total Pages : 123 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning by : ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.)

Download or read book Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning written by ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.) and published by Springer Nature. This book was released on 2024 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth investigation into the complexities of long-term structural health monitoring (SHM) in civil structures, specifically focusing on the challenges posed by small data and environmental and operational changes (EOCs). Traditional contact-based sensor networks in SHM produce large amounts of data, complicating big data management. In contrast, synthetic aperture radar (SAR)-aided SHM often faces challenges with small datasets and limited displacement data. Additionally, EOCs can mimic the structural damage, resulting in false errors that can critically affect economic and safety issues. Addressing these challenges, this book introduces seven advanced unsupervised learning methods for SHM, combining AI, data sampling, and statistical analysis. These include techniques for managing datasets and addressing EOCs. Methods range from nearest neighbor searching and Hamiltonian Monte Carlo sampling to innovative offline and online learning frameworks, focusing on data augmentation and normalization. Key approaches involve deep autoencoders for data processing and novel algorithms for damage detection. Validated using simulated data from the I-40 Bridge, USA, and real-world data from the Tadcaster Bridge, UK, these methods show promise in addressing SAR-aided SHM challenges, offering practical tools for real-world applications. The book, thereby, presents a comprehensive suite of innovative strategies to advance the field of SHM.

Machine Learning and Knowledge Discovery in Databases

Author : Peggy Cellier
Publisher : Springer Nature
ISBN 13 : 3030438872
Total Pages : 755 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Peggy Cellier

Download or read book Machine Learning and Knowledge Discovery in Databases written by Peggy Cellier and published by Springer Nature. This book was released on 2020-03-27 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set constitutes the refereed proceedings of the workshops which complemented the 19th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in Würzburg, Germany, in September 2019. The 70 full papers and 46 short papers presented in the two-volume set were carefully reviewed and selected from 200 submissions. The two volumes (CCIS 1167 and CCIS 1168) present the papers that have been accepted for the following workshops: Workshop on Automating Data Science, ADS 2019; Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence and eXplainable Knowledge Discovery in Data Mining, AIMLAI-XKDD 2019; Workshop on Decentralized Machine Learning at the Edge, DMLE 2019; Workshop on Advances in Managing and Mining Large Evolving Graphs, LEG 2019; Workshop on Data and Machine Learning Advances with Multiple Views; Workshop on New Trends in Representation Learning with Knowledge Graphs; Workshop on Data Science for Social Good, SoGood 2019; Workshop on Knowledge Discovery and User Modelling for Smart Cities, UMCIT 2019; Workshop on Data Integration and Applications Workshop, DINA 2019; Workshop on Machine Learning for Cybersecurity, MLCS 2019; Workshop on Sports Analytics: Machine Learning and Data Mining for Sports Analytics, MLSA 2019; Workshop on Categorising Different Types of Online Harassment Languages in Social Media; Workshop on IoT Stream for Data Driven Predictive Maintenance, IoTStream 2019; Workshop on Machine Learning and Music, MML 2019; Workshop on Large-Scale Biomedical Semantic Indexing and Question Answering, BioASQ 2019.

Biometrics—Advances in Research and Application: 2013 Edition

Author :
Publisher : ScholarlyEditions
ISBN 13 : 1481673556
Total Pages : 142 pages
Book Rating : 4.4/5 (816 download)

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Book Synopsis Biometrics—Advances in Research and Application: 2013 Edition by :

Download or read book Biometrics—Advances in Research and Application: 2013 Edition written by and published by ScholarlyEditions. This book was released on 2013-06-21 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biometrics—Advances in Research and Application: 2013 Edition is a ScholarlyBrief™ that delivers timely, authoritative, comprehensive, and specialized information about ZZZAdditional Research in a concise format. The editors have built Biometrics—Advances in Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about ZZZAdditional Research in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Biometrics—Advances in Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Bridging the Gap between Machine Learning and Affective Computing

Author : Zhen Cui
Publisher : Frontiers Media SA
ISBN 13 : 2832503799
Total Pages : 151 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Bridging the Gap between Machine Learning and Affective Computing by : Zhen Cui

Download or read book Bridging the Gap between Machine Learning and Affective Computing written by Zhen Cui and published by Frontiers Media SA. This book was released on 2023-01-05 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affective computing refers to computing that relates to, arises from, or influences emotions, as pioneered by Rosalind Picard in 1995. The goal of affective computing is to bridge the gap between human and machines and ultimately enable robots to communicate with human naturally and emotionally. Recently, the research on affective computing has gained considerable progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing mainly focuses on estimating of human emotions through different forms of signals, e.g., face video, EEG, Speech, PET scans or fMRI. Inferring the emotion of humans is difficult, as emotion is a subjective, unconscious experience characterized primarily by psycho-physiological expressions and biological reactions. It is influenced by hormones and neurotransmitters such as dopamine, noradrenaline, serotonin, oxytocin, GABA… etc. The physiology of emotion is closely linked to arousal of the nervous system with various states and strengths relating, apparently, to different particular emotions. To understand “emotion” or “affect” merely by machine learning or big data analysis is not enough, but the understanding and applications from the intrinsic features of emotions from the neuroscience aspect is essential.

Independent Component Analysis

Author : James V. Stone
Publisher : MIT Press
ISBN 13 : 9780262693158
Total Pages : 224 pages
Book Rating : 4.6/5 (931 download)

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Book Synopsis Independent Component Analysis by : James V. Stone

Download or read book Independent Component Analysis written by James V. Stone and published by MIT Press. This book was released on 2004 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: A tutorial-style introduction to a class of methods for extracting independent signals from a mixture of signals originating from different physical sources; includes MatLab computer code examples. Independent component analysis (ICA) is becoming an increasingly important tool for analyzing large data sets. In essence, ICA separates an observed set of signal mixtures into a set of statistically independent component signals, or source signals. In so doing, this powerful method can extract the relatively small amount of useful information typically found in large data sets. The applications for ICA range from speech processing, brain imaging, and electrical brain signals to telecommunications and stock predictions. In Independent Component Analysis, Jim Stone presents the essentials of ICA and related techniques (projection pursuit and complexity pursuit) in a tutorial style, using intuitive examples described in simple geometric terms. The treatment fills the need for a basic primer on ICA that can be used by readers of varying levels of mathematical sophistication, including engineers, cognitive scientists, and neuroscientists who need to know the essentials of this evolving method. An overview establishes the strategy implicit in ICA in terms of its essentially physical underpinnings and describes how ICA is based on the key observations that different physical processes generate outputs that are statistically independent of each other. The book then describes what Stone calls "the mathematical nuts and bolts" of how ICA works. Presenting only essential mathematical proofs, Stone guides the reader through an exploration of the fundamental characteristics of ICA. Topics covered include the geometry of mixing and unmixing; methods for blind source separation; and applications of ICA, including voice mixtures, EEG, fMRI, and fetal heart monitoring. The appendixes provide a vector matrix tutorial, plus basic demonstration computer code that allows the reader to see how each mathematical method described in the text translates into working Matlab computer code.

Web and Big Data

Author : Xin Wang
Publisher : Springer Nature
ISBN 13 : 3030602591
Total Pages : 829 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Web and Big Data by : Xin Wang

Download or read book Web and Big Data written by Xin Wang and published by Springer Nature. This book was released on 2020-10-15 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set, LNCS 11317 and 12318, constitutes the thoroughly refereed proceedings of the 4th International Joint Conference, APWeb-WAIM 2020, held in Tianjin, China, in September 2020. Due to the COVID-19 pandemic the conference was organizedas a fully online conference. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions. The papers are organized around the following topics: Big Data Analytics; Graph Data and Social Networks; Knowledge Graph; Recommender Systems; Information Extraction and Retrieval; Machine Learning; Blockchain; Data Mining; Text Analysis and Mining; Spatial, Temporal and Multimedia Databases; Database Systems; and Demo.

Computer Vision – ECCV 2018

Author : Vittorio Ferrari
Publisher : Springer
ISBN 13 : 303001228X
Total Pages : 861 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Computer Vision – ECCV 2018 by : Vittorio Ferrari

Download or read book Computer Vision – ECCV 2018 written by Vittorio Ferrari and published by Springer. This book was released on 2018-10-06 with total page 861 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Audio Source Separation and Speech Enhancement

Author : Emmanuel Vincent
Publisher : John Wiley & Sons
ISBN 13 : 1119279895
Total Pages : 517 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Audio Source Separation and Speech Enhancement by : Emmanuel Vincent

Download or read book Audio Source Separation and Speech Enhancement written by Emmanuel Vincent and published by John Wiley & Sons. This book was released on 2018-10-22 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the technology behind hearing aids, Siri, and Echo Audio source separation and speech enhancement aim to extract one or more source signals of interest from an audio recording involving several sound sources. These technologies are among the most studied in audio signal processing today and bear a critical role in the success of hearing aids, hands-free phones, voice command and other noise-robust audio analysis systems, and music post-production software. Research on this topic has followed three convergent paths, starting with sensor array processing, computational auditory scene analysis, and machine learning based approaches such as independent component analysis, respectively. This book is the first one to provide a comprehensive overview by presenting the common foundations and the differences between these techniques in a unified setting. Key features: Consolidated perspective on audio source separation and speech enhancement. Both historical perspective and latest advances in the field, e.g. deep neural networks. Diverse disciplines: array processing, machine learning, and statistical signal processing. Covers the most important techniques for both single-channel and multichannel processing. This book provides both introductory and advanced material suitable for people with basic knowledge of signal processing and machine learning. Thanks to its comprehensiveness, it will help students select a promising research track, researchers leverage the acquired cross-domain knowledge to design improved techniques, and engineers and developers choose the right technology for their target application scenario. It will also be useful for practitioners from other fields (e.g., acoustics, multimedia, phonetics, and musicology) willing to exploit audio source separation or speech enhancement as pre-processing tools for their own needs.

New Innovations in AI, Aviation, and Air Traffic Technology

Author : Khalid, Saifullah
Publisher : IGI Global
ISBN 13 :
Total Pages : 552 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis New Innovations in AI, Aviation, and Air Traffic Technology by : Khalid, Saifullah

Download or read book New Innovations in AI, Aviation, and Air Traffic Technology written by Khalid, Saifullah and published by IGI Global. This book was released on 2024-07-17 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancement of technology, along with the increasing complexity of air traffic management present significant challenges in aviation management. As the industry continues to evolve, aviation professionals must stay updated with the latest advancements to ensure safe and efficient operations. However, accessing comprehensive and up-to-date resources can be difficult, leading to a knowledge gap that hinders the industry's progress. New Innovations in AI, Aviation, and Air Traffic Technology offers a solution to the challenges faced by aviation management professionals by providing a comprehensive overview of futuristic research trends in aviation management. Through case studies, simulations, and experimental results, we offer readers a detailed exploration of the latest trends in air traffic management, uncrewed aerial vehicles (UAVs), electric vehicles, and more. By providing a bridge between theory and practice, this book equips aviation professionals with the knowledge and tools needed to navigate and contribute to the rapidly evolving aviation industry.

Deep Learning Concepts in Operations Research

Author : Biswadip Basu Mallik
Publisher : CRC Press
ISBN 13 : 1040102360
Total Pages : 277 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Deep Learning Concepts in Operations Research by : Biswadip Basu Mallik

Download or read book Deep Learning Concepts in Operations Research written by Biswadip Basu Mallik and published by CRC Press. This book was released on 2024-08-30 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines: An overview of applications and computing devices Deep learning impacts in the field of AI Deep learning as state-of-the-art approach to AI Exploring deep learning architecture for cutting-edge AI solutions Operations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost.

Progress in Advanced Computing and Intelligent Engineering

Author : Bibudhendu Pati
Publisher : Springer
ISBN 13 : 9811317089
Total Pages : 585 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Progress in Advanced Computing and Intelligent Engineering by : Bibudhendu Pati

Download or read book Progress in Advanced Computing and Intelligent Engineering written by Bibudhendu Pati and published by Springer. This book was released on 2018-12-17 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gathers high-quality research papers presented at the International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2017). It includes technical sections describing progress in the fields of advanced computing and intelligent engineering, and is primarily intended for postgraduate students and researchers working in Computer Science and Engineering. However, researchers working in Electronics will also find the book useful, as it addresses hardware technologies and next-gen communication technologies.

Neural information processing [electronic resource]

Author : Nikil R. Pal
Publisher : Springer Science & Business Media
ISBN 13 : 3540239316
Total Pages : 1397 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Neural information processing [electronic resource] by : Nikil R. Pal

Download or read book Neural information processing [electronic resource] written by Nikil R. Pal and published by Springer Science & Business Media. This book was released on 2004-11-18 with total page 1397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation This book constitutes the refereed proceedings of the 11th International Conference on Neural Information Processing, ICONIP 2004, held in Calcutta, India in November 2004. The 186 revised papers presented together with 24 invited contributions were carefully reviewed and selected from 470 submissions. The papers are organized in topical sections on computational neuroscience, complex-valued neural networks, self-organizing maps, evolutionary computation, control systems, cognitive science, adaptive intelligent systems, biometrics, brain-like computing, learning algorithms, novel neural architectures, image processing, pattern recognition, neuroinformatics, fuzzy systems, neuro-fuzzy systems, hybrid systems, feature analysis, independent component analysis, ant colony, neural network hardware, robotics, signal processing, support vector machine, time series prediction, and bioinformatics.

Emerging Research in Data Engineering Systems and Computer Communications

Author : P. Venkata Krishna
Publisher : Springer Nature
ISBN 13 : 9811501351
Total Pages : 675 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Emerging Research in Data Engineering Systems and Computer Communications by : P. Venkata Krishna

Download or read book Emerging Research in Data Engineering Systems and Computer Communications written by P. Venkata Krishna and published by Springer Nature. This book was released on 2020-02-10 with total page 675 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the 2nd International Conference on Computing, Communications and Data Engineering, held at Sri Padmavati Mahila Visvavidyalayam, Tirupati, India from 1 to 2 Feb 2019. Chiefly discussing major issues and challenges in data engineering systems and computer communications, the topics covered include wireless systems and IoT, machine learning, optimization, control, statistics, and social computing.