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Machine Component Analysis With Matlab

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Machine Component Analysis with MATLAB

Machine Component Analysis with MATLAB Book
Author : Dan B. Marghitu,Mihai Dupac
Publisher : Butterworth-Heinemann
Release : 2019-03-15
ISBN : 012804229X
Language : En, Es, Fr & De

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Book Description :

Machine Design Analysis with MATLAB is a highly practical guide to the fundamental principles of machine design which covers the static and dynamic behavior of engineering structures and components. MATLAB has transformed the way calculations are made for engineering problems by computationally generating analytical calculations, as well as providing numerical calculations. Using step-by-step, real world example problems, this book demonstrates how you can use symbolic and numerical MATLAB as a tool to solve problems in machine design. This book provides a thorough, rigorous presentation of machine design, augmented with proven learning techniques which can be used by students and practicing engineers alike. Comprehensive coverage of the fundamental principles in machine design Uses symbolical and numerical MATLAB calculations to enhance understanding and reinforce learning Includes well-designed real-world problems and solutions

Machine Component Analysis with MATLAB

Machine Component Analysis with MATLAB Book
Author : Dan B. Marghitu,Mihai Dupac
Publisher : Butterworth-Heinemann
Release : 2019-02-12
ISBN : 0128042451
Language : En, Es, Fr & De

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Book Description :

Machine Design Analysis with MATLAB is a highly practical guide to the fundamental principles of machine design which covers the static and dynamic behavior of engineering structures and components. MATLAB has transformed the way calculations are made for engineering problems by computationally generating analytical calculations, as well as providing numerical calculations. Using step-by-step, real world example problems, this book demonstrates how you can use symbolic and numerical MATLAB as a tool to solve problems in machine design. This book provides a thorough, rigorous presentation of machine design, augmented with proven learning techniques which can be used by students and practicing engineers alike. Comprehensive coverage of the fundamental principles in machine design Uses symbolical and numerical MATLAB calculations to enhance understanding and reinforce learning Includes well-designed real-world problems and solutions

Mechanical Simulation with MATLAB

Mechanical Simulation with MATLAB   Book
Author : Dan B. Marghitu
Publisher : Springer Nature
Release : 2022-01-24
ISBN : 3030881024
Language : En, Es, Fr & De

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Book Description :

Download Mechanical Simulation with MATLAB book written by Dan B. Marghitu, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Mechanical Design of Machine Components

Mechanical Design of Machine Components Book
Author : Ansel C. Ugural
Publisher : Taylor & Francis
Release : 2018-09-03
ISBN : 1315362260
Language : En, Es, Fr & De

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Book Description :

Analyze and Solve Real-World Machine Design Problems Using SI Units Mechanical Design of Machine Components, Second Edition: SI Version strikes a balance between method and theory, and fills a void in the world of design. Relevant to mechanical and related engineering curricula, the book is useful in college classes, and also serves as a reference for practicing engineers. This book combines the needed engineering mechanics concepts, analysis of various machine elements, design procedures, and the application of numerical and computational tools. It demonstrates the means by which loads are resisted in mechanical components, solves all examples and problems within the book using SI units, and helps readers gain valuable insight into the mechanics and design methods of machine components. The author presents structured, worked examples and problem sets that showcase analysis and design techniques, includes case studies that present different aspects of the same design or analysis problem, and links together a variety of topics in successive chapters. SI units are used exclusively in examples and problems, while some selected tables also show U.S. customary (USCS) units. This book also presumes knowledge of the mechanics of materials and material properties. New in the Second Edition: Presents a study of two entire real-life machines Includes Finite Element Analysis coverage supported by examples and case studies Provides MATLAB solutions of many problem samples and case studies included on the book’s website Offers access to additional information on selected topics that includes website addresses and open-ended web-based problems Class-tested and divided into three sections, this comprehensive book first focuses on the fundamentals and covers the basics of loading, stress, strain, materials, deflection, stiffness, and stability. This includes basic concepts in design and analysis, as well as definitions related to properties of engineering materials. Also discussed are detailed equilibrium and energy methods of analysis for determining stresses and deformations in variously loaded members. The second section deals with fracture mechanics, failure criteria, fatigue phenomena, and surface damage of components. The final section is dedicated to machine component design, briefly covering entire machines. The fundamentals are applied to specific elements such as shafts, bearings, gears, belts, chains, clutches, brakes, and springs.

Introduction to Statistical Machine Learning

Introduction to Statistical Machine Learning Book
Author : Masashi Sugiyama
Publisher : Morgan Kaufmann
Release : 2015-10-31
ISBN : 0128023503
Language : En, Es, Fr & De

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Book Description :

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials. Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks. Provides the necessary background material to understand machine learning such as statistics, probability, linear algebra, and calculus. Complete coverage of the generative approach to statistical pattern recognition and the discriminative approach to statistical machine learning. Includes MATLAB/Octave programs so that readers can test the algorithms numerically and acquire both mathematical and practical skills in a wide range of data analysis tasks Discusses a wide range of applications in machine learning and statistics and provides examples drawn from image processing, speech processing, natural language processing, robot control, as well as biology, medicine, astronomy, physics, and materials.

Advances in Automation Signal Processing Instrumentation and Control

Advances in Automation  Signal Processing  Instrumentation  and Control Book
Author : Venkata Lakshmi Narayana Komanapalli,N. Sivakumaran,Santoshkumar Hampannavar
Publisher : Springer Nature
Release : 2021-03-04
ISBN : 9811582211
Language : En, Es, Fr & De

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Book Description :

This book presents the select proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (i-CASIC) 2020. The book mainly focuses on emerging technologies in electrical systems, IoT-based instrumentation, advanced industrial automation, and advanced image and signal processing. It also includes studies on the analysis, design and implementation of instrumentation systems, and high-accuracy and energy-efficient controllers. The contents of this book will be useful for beginners, researchers as well as professionals interested in instrumentation and control, and other allied fields.

Brain and Behavior Computing

Brain and Behavior Computing Book
Author : Mridu Sahu,G R Sinha
Publisher : CRC Press
Release : 2021-06-24
ISBN : 1000387151
Language : En, Es, Fr & De

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Book Description :

Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it’s working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing.

Machine Learning

Machine Learning Book
Author : Yagang Zhang
Publisher : BoD – Books on Demand
Release : 2010-02-01
ISBN : 9533070331
Language : En, Es, Fr & De

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Book Description :

Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge about machine learning and practice presented in the book, it is divided into three major parts: Introduction, Machine Learning Theory and Applications. Part I focuses on the introduction to machine learning. The author also attempts to promote a new design of thinking machines and development philosophy. Considering the growing complexity and serious difficulties of information processing in machine learning, in Part II of the book, the theoretical foundations of machine learning are considered, and they mainly include self-organizing maps (SOMs), clustering, artificial neural networks, nonlinear control, fuzzy system and knowledge-based system (KBS). Part III contains selected applications of various machine learning approaches, from flight delays, network intrusion, immune system, ship design to CT and RNA target prediction. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners.

Engineering Applications

Engineering Applications Book
Author : Mihai Dupac,Dan B. Marghitu
Publisher : John Wiley & Sons
Release : 2021-03-03
ISBN : 1119093635
Language : En, Es, Fr & De

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Book Description :

A comprehensive text on the fundamental principles of mechanical engineering Engineering Applications presents a comprehensive text to the fundamental principles and applications of the statics and mechanics of materials in the design of complex mechanical systems. The book uses the modern tool of MATLAB to help solve problems with numerical and analytical calculations. The authors—noted experts on the topic—offer an understanding of the static behaviour of engineering structures and components considering the mechanics of materials knowledge as an essential part (most important) for their design. The authors explore the concepts, derivations and interpretations of the general principles and discuss the creation of mathematical models and the formulation of the mathematical equations. The practical text highlights the solutions of the problems that are solved analytically and numerically using MATLAB. The figures generated with MATLAB reinforce visual learning for students (and professionals) as they study the programs. This important text: Shows how mechanical principles are applied to engineering design Covers basic material with both mathematical and physical insight Provides an understanding of classical mechanical principles Offers the modern tool of MATLAB to solve problems Helps to reinforce learning using visual and computational techniques Written for students and professional mechanical engineers, Engineering Applications helps hone reasoning skills in order to interpret data, generate mathematical equations and learn different methods of solving them for evaluating and designing engineering systems.

Independent Component Analysis and Blind Signal Separation

Independent Component Analysis and Blind Signal Separation Book
Author : Carlos G. Puntonet
Publisher : Springer Science & Business Media
Release : 2004-09-17
ISBN : 3540230564
Language : En, Es, Fr & De

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Book Description :

tionsalso,apartfromsignalprocessing,withother?eldssuchasstatisticsandarti?cial neuralnetworks. As long as we can ?nd a system that emits signals propagated through a mean, andthosesignalsarereceivedbyasetofsensorsandthereisaninterestinrecovering the originalsources,we have a potential?eld ofapplication forBSS and ICA. Inside thatwiderangeofapplicationswecan?nd,forinstance:noisereductionapplications, biomedicalapplications,audiosystems,telecommunications,andmanyothers. This volume comes out just 20 years after the ?rst contributionsin ICA and BSS 1 appeared . Thereinafter,the numberof research groupsworking in ICA and BSS has been constantly growing, so that nowadays we can estimate that far more than 100 groupsareresearchinginthese?elds. Asproofoftherecognitionamongthescienti?ccommunityofICAandBSSdev- opmentstherehavebeennumerousspecialsessionsandspecialissuesinseveralwell- 1 J.Herault, B.Ans,“Circuits neuronaux à synapses modi?ables: décodage de messages c- posites para apprentissage non supervise”, C.R. de l'Académie des Sciences, vol. 299, no. III-13,pp.525–528,1984.

Machine Learning

Machine Learning Book
Author : Sergios Theodoridis
Publisher : Academic Press
Release : 2015-04-02
ISBN : 0128017228
Language : En, Es, Fr & De

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Book Description :

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques – together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods. The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling. Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied. MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.

Condition Monitoring with Vibration Signals

Condition Monitoring with Vibration Signals Book
Author : Asoke K. Nandi,Hosameldin Ahmed
Publisher : John Wiley & Sons
Release : 2019-10-16
ISBN : 1119544637
Language : En, Es, Fr & De

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Book Description :

Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoring—guiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.

Predictive Modeling of Drug Sensitivity

Predictive Modeling of Drug Sensitivity Book
Author : Ranadip Pal
Publisher : Academic Press
Release : 2016-11-15
ISBN : 012805431X
Language : En, Es, Fr & De

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Book Description :

Predictive Modeling of Drug Sensitivity gives an overview of drug sensitivity modeling for personalized medicine that includes data characterizations, modeling techniques, applications, and research challenges. It covers the major mathematical techniques used for modeling drug sensitivity, and includes the requisite biological knowledge to guide a user to apply the mathematical tools in different biological scenarios. This book is an ideal reference for computer scientists, engineers, computational biologists, and mathematicians who want to understand and apply multiple approaches and methods to drug sensitivity modeling. The reader will learn a broad range of mathematical and computational techniques applied to the modeling of drug sensitivity, biological concepts, and measurement techniques crucial to drug sensitivity modeling, how to design a combination of drugs under different constraints, and the applications of drug sensitivity prediction methodologies. Applies mathematical and computational approaches to biological problems Covers all aspects of drug sensitivity modeling, starting from initial data generation to final experimental validation Includes the latest results on drug sensitivity modeling that is based on updated research findings Provides information on existing data and software resources for applying the mathematical and computational tools available

Face Perception across the Life Span

Face Perception across the Life Span Book
Author : Bozana Meinhardt-Injac,Andrea Hildebrandt
Publisher : Frontiers Media SA
Release : 2017-03-17
ISBN : 2889451143
Language : En, Es, Fr & De

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Book Description :

Face perception is a highly evolved visual skills in humans. This complex ability develops across the life-span, steeply rising in infancy, refining across childhood and adolescence, reaching highest levels in adulthood and declining in old age. As such, the development of face perception comprises multiple skills, including sensory (e.g., mechanisms of holistic, configural and featural perception), cognitive (e.g., memory, processing speed, attentional control), and also emotional and social (e.g., reading and interpreting facial expression) domains. Whereas our understanding of specific functional domains involved in face perception is growing, there is further pressing demand for a multidisciplinary approach toward a more integrated view, describing how face perception ability relates to and develops with other domains of sensory and cognitive functioning. In this research topic we bring together a collection of papers that provide a shot of the current state of the art of theorizing and investigating face perception from the perspective of multiple ability domains. We would like to thank all authors for their valuable contributions that advanced our understanding of face and emotion perception across development.

Independent Component Analysis and Signal Separation

Independent Component Analysis and Signal Separation Book
Author : Tulay Adali,Christian Jutten,Joao Marcos Travassos Romano,Allan Kardec Barros
Publisher : Springer Science & Business Media
Release : 2009-02-25
ISBN : 3642005985
Language : En, Es, Fr & De

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Book Description :

This volume contains the papers presented at the 8th International Conf- ence on Independent Component Analysis (ICA) and Source Separation held in Paraty, Brazil, March 15–18, 2009. This year's event resulted from scienti?c collaborations between a team of researchers from ?ve di?erent Brazilian u- versities and received the support of the Brazilian Telecommunications Society (SBrT) as well as the ?nancial sponsorship of CNPq, CAPES and FAPERJ. Independent component analysis and signal separation is one of the most - citing current areas of research in statistical signal processing and unsupervised machine learning. The area has received attention from severalresearchcom- nities including machine learning, neural networks, statistical signal processing and Bayesian modeling. Independent component analysis and signal separation has applications at the intersection of many science and engineering disciplines concerned with understanding and extracting useful information from data as diverse as neuronal activity and brain images, bioinformatics, communications, the World Wide Web, audio, video, sensor signals, and time series.

MATLAB for Machine Learning

MATLAB for Machine Learning Book
Author : Giuseppe Ciaburro
Publisher : Packt Publishing Ltd
Release : 2017-08-28
ISBN : 1788399390
Language : En, Es, Fr & De

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Book Description :

Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Molecular breeding for the genetic improvement of forage crops and turf

Molecular breeding for the genetic improvement of forage crops and turf Book
Author : M. Humphreys
Publisher : Wageningen Academic Publishers
Release : 2005-06-17
ISBN : 9086865550
Language : En, Es, Fr & De

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Book Description :

Grassland covers 26% of the world’s total land area. It produces feed for livestock; maintains soil fertility; protects and conserves soil and water resources; creates a habitat for wildlife; provides recreational space for sport and leisure and contributes to the general landscape. This book provides an up-to-date account of progress and potential in the genetic improvement of grassland to meet all needs. It encompasses work on a wide range of temperate and tropical grassland species (including grasses, clovers and other forage legumes) and will interest all those concerned with grassland use in livestock-based agriculture, recreation, environmental protection, bio-industry etc. Specifically, it demonstrates how recent advances in molecular techniques are being used to develop breeding objectives and strategies with key-note papers on: Objectives and benefits of molecular breeding, Linkage/physical mapping and map-based cloning, QTL analysis and trait dissection, Genomics, model species, gene discovery and functional analysis, Use of molecular markers and bioinformatics for breeding, Molecular genetics and breeding of endosymbiont and grass/legume associations, Transgenics, Genetic diversity, breeding systems and resources Future directions for research and breeding. State-of-the-art molecular techniques and resources are described that encompass a unique range of expertise in genetic mapping, trait dissection, comparative genomics, bioinformatics, gene discovery and risk assessment. Examples of work in progress or recently completed are provided from across the world. The book has broad educational value and will interest plant geneticists and breeders as well as grassland users and policy makers.

Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications Book
Author : Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch
Publisher : Academic Press
Release : 2019-11-29
ISBN : 0128144831
Language : En, Es, Fr & De

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Book Description :

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Advances in VLSI Signal Processing Power Electronics IoT Communication and Embedded Systems

Advances in VLSI  Signal Processing  Power Electronics  IoT  Communication and Embedded Systems Book
Author : Shubhakar Kalya,Muralidhar Kulkarni,K. S. Shivaprakasha
Publisher : Springer Nature
Release : 2021-05-12
ISBN : 9811604436
Language : En, Es, Fr & De

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Book Description :

This book comprises select peer-reviewed papers from the International Conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems (VSPICE-2020). The book provides insights into various aspects of the emerging fields in the areas Electronics and Communication Engineering as a holistic approach. The various topics covered in this book include VLSI, embedded systems, signal processing, communication, power electronics and internet of things. This book mainly focuses on the most recent innovations, trends, concerns and practical challenges and their solutions. This book will be useful for academicians, professionals and researchers in the area of electronics and communications and electrical engineering.

MATLAB

MATLAB Book
Author : Vasilios Katsikis
Publisher : BoD – Books on Demand
Release : 2012-09-26
ISBN : 9535107518
Language : En, Es, Fr & De

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Book Description :

This excellent book represents the second part of three-volumes regarding MATLAB- based applications in almost every branch of science. The present textbook contains a collection of 13 exceptional articles. In particular, the book consists of three sections, the first one is devoted to electronic engineering and computer science, the second is devoted to MATLAB/SIMULINK as a tool for engineering applications, the third one is about Telecommunication and communication systems and the last one discusses MATLAB toolboxes.