Download or read book Backpropagation written by Yves Chauvin and published by Psychology Press. This book was released on 2013-02-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.

Download or read book The Roots of Backpropagation written by Paul John Werbos and published by John Wiley & Sons. This book was released on 1994-03-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now, for the first time, publication of the landmark work inbackpropagation! Scientists, engineers, statisticians, operationsresearchers, and other investigators involved in neural networkshave long sought direct access to Paul Werbos's groundbreaking,much-cited 1974 Harvard doctoral thesis, The Roots ofBackpropagation, which laid the foundation of backpropagation. Now,with the publication of its full text, these practitioners can gostraight to the original material and gain a deeper, practicalunderstanding of this unique mathematical approach to socialstudies and related fields. In addition, Werbos has provided threemore recent research papers, which were inspired by his originalwork, and a new guide to the field. Originally written for readerswho lacked any knowledge of neural nets, The Roots ofBackpropagation firmly established both its historical andcontinuing significance as it: * Demonstrates the ongoing value and new potential ofbackpropagation * Creates a wealth of sound mathematical tools useful acrossdisciplines * Sets the stage for the emerging area of fast automaticdifferentiation * Describes new designs for forecasting and control which exploitbackpropagation * Unifies concepts from Freud, Jung, biologists, and others into anew mathematical picture of the human mind and how it works * Certifies the viability of Deutsch's model of nationalism as apredictive tool--as well as the utility of extensions of thiscentral paradigm "What a delight it was to see Paul Werbos rediscover Freud'sversion of 'back-propagation.' Freud was adamant (in The Projectfor a Scientific Psychology) that selective learning could onlytake place if the presynaptic neuron was as influenced as is thepostsynaptic neuron during excitation. Such activation of bothsides of the contact barrier (Freud's name for the synapse) wasaccomplished by reducing synaptic resistance by the absorption of'energy' at the synaptic membranes. Not bad for 1895! But Werbos1993 is even better." --Karl H. Pribram Professor Emeritus,Stanford University

Download or read book Neural Networks written by Raul Rojas and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Download or read book Backpropagation written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-21 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Backpropagation Backpropagation is a technique for machine learning that uses a backward pass to update the model's parameters. The goal of the algorithm is to reduce the mean squared error (MSE) as much as possible. The following actions are taken during backpropagation in a network with a single layer:Follow the path through the network from the input all the way to the output by computing the output of the hidden layers as well as the output layer. [This Is the Step of Feedforward]Calculate the derivative of the cost function with respect to the input layer and the hidden layers using the information available in the output layer.Repeatedly update the weights until they converge or sufficient iterations have been applied to the model, whichever comes first. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Backpropagation Chapter 2: Chain rule Chapter 3: Perceptron Chapter 4: Artificial neuron Chapter 5: Total derivative Chapter 6: Delta rule Chapter 7: Feedforward neural network Chapter 8: Multilayer perceptron Chapter 9: Vanishing gradient problem Chapter 10: Mathematics of artificial neural networks (II) Answering the public top questions about backpropagation. (III) Real world examples for the usage of backpropagation in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of backpropagation. What Is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.

Download or read book Learn From Scratch Backpropagation Neural Networks Using Python GUI MariaDB written by Hamzan Wadi and published by Turida Publisher. This book was released on with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical explanation of the backpropagation neural networks and how it can be implemented for data prediction and data classification. The discussion in this book is presented in step by step so that it will help readers understand the fundamental of the backpropagation neural networks and its steps. This book is very suitable for students, researchers, and anyone who want to learn and implement the backpropagation neural networks for data prediction and data classification using PYTHON GUI and MariaDB. The discussion in this book will provide readers deep understanding about the backpropagation neural networks architecture and its parameters. The readers will be guided to understand the steps of the backpropagation neural networks for data prediction and data classification through case examples. In addition, readers are also guided step by step to implement the backpropagation neural networks for data prediction and data classification using PYTHON GUI and MariaDB. The readers will be guided to create their own backpropagation neural networks class and build their complete applications for data prediction and data classification. This book consists of three cases which are realized into complete projects using the Python GUI and MariaDB. The three cases that will be learned in this book are as follow. 1. Sales prediction using the backpropagation neural networks. 2. Earthquake data prediction using the backpropagation neural networks. 3. Fruit quality classification using the backpropagation neural networks. Each case in this book is equipped with a mathematical calculation that will help the reader understand each step that must be taken. The cases in this book are realized into three types of applications which are command window based application, GUI based application, and database application using Python GUI and MariaDB. The final result of this book is that the readers are able to realize each step of the backpropagation neural networks for data prediction and data classification. In Addition, the readers also are able to create the backpropagation neural networks applications which consists of three types of applications which are command window based application, GUI based application, and database application using Python GUI and MariaDB.

Download or read book New Backpropagation Algorithm with Type 2 Fuzzy Weights for Neural Networks written by Fernando Gaxiola and published by Springer. This book was released on 2016-06-02 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ô=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.

Download or read book Parallel Implementations of Backpropagation Neural Networks on Transputers written by P. Saratchandran and published by World Scientific. This book was released on 1996 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted.

Download or read book Advances in Neural Networks written by Fuchun Sun and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 939 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.

Download or read book Biological and Biomedical Infrared Spectroscopy written by A. Barth and published by IOS Press. This book was released on 2009-09-02 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although infrared spectroscopy has been applied with success to the study of important biological and biomedical processes for many years, key advances in this vibrant technique have led to its increasing use, ranging from characterisation of individual macromolecules (DNA, RNA, lipids, proteins) to human tissues, cells and their components. Infrared spectroscopy thus has a significant role to play in the analysis of the vast number of genes and proteins being identified by the various genomic sequencing projects. Whilst this book gives an overview of the field it highlights more recent developments, such as the use of bright synchrotron radiation for recording infrared spectra, the development of two-dimensional infrared spectroscopy and the ability to record infrared spectra at ultrafast speeds. The main focus is on the mid-infrared region, since the great majority of studies are carried out in this region but there is increasing use of the near infrared for biomedical applications and a chapter is devoted to this part of the spectrum. Major advances in theoretical analysis have also enabled better interpretation of the infrared spectra of biological molecules and these are covered. The editors, Professor Andreas Barth of Stockholm University, Stockholm, Sweden and Dr Parvez I. Haris of De Montfort University, Leicester, U.K., who both have extensive research experience in biological infrared spectroscopy per se and in its use in the solution of biophysical problems, have felt it timely therefore to bring together this book. The book is intended for use both by research scientists already active in the use of biological infrared spectroscopy and for those coming new to the technique. Graduate students will also find it useful as an introduction to the technique.

Download or read book Machine Learning written by Mr. Y. David Solomon Raju, M. Tech, (Ph. D.), LMISTE, LMISOI, FIETE, MIE, MIAENG, Associate Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) and published by GCS PUBLISHERS. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning WRITTEN BY Y. David Solomon Raju, K. Shyamala, Ch. Sumalatha

Download or read book Neural Networks for Hydrological Modeling written by Robert Abrahart and published by CRC Press. This book was released on 2004-05-15 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The b

Download or read book Introduction to Artificial Neural Networks written by Dr.T.Arumuga Maria Devi and published by SK Research Group of Companies. This book was released on 2022-11-15 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.T.Arumuga Maria Devi, Assistant Professor, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mr.A.Chockalingam, Assistant Professor Temp. and Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India. Mrs.P.Thangaselvi , Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India. Dr.M.Santhanakumar, Assistant Professor Temp., Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.R.Hepzibai , Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India.

Download or read book Applied Big Data Analytics in Operations Management written by Kumar, Manish and published by IGI Global. This book was released on 2016-09-30 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Download or read book R Mining spatial text web and social media data written by Bater Makhabel and published by Packt Publishing Ltd. This book was released on 2017-06-19 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Data Mining with R by Bater Makhabel R Data Mining Blueprints by Pradeepta Mishra Social Media Mining with R by Nathan Danneman and Richard Heimann Style and approach A complete package with which will take you from the basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.

Download or read book Internet of Things for Architects written by Perry Lea and published by Packt Publishing Ltd. This book was released on 2018-01-22 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to design, implement and secure your IoT infrastructure Key Features Build a complete IoT system that is the best fit for your organization Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack Understand the theory, concepts, and implementation of each element that comprises IoT design—from sensors to the cloud Implement best practices to ensure the reliability, scalability, robust communication systems, security, and data analysis in your IoT infrastructure Book Description The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is necessary if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of devices. This book encompasses the entire spectrum of IoT solutions, from sensors to the cloud. We start by examining modern sensor systems and focus on their power and functionality. After that, we dive deep into communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, we explore IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, SigFox, and LoRaWAN. Next, we cover edge routing and gateways and their role in fog computing, as well as the messaging protocols of MQTT and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. We wrap up the analytics portion of the book with the application of statistical analysis, complex event processing, and deep learning models. Finally, we conclude by providing a holistic view of the IoT security stack and the anatomical details of IoT exploits while countering them with software defined perimeters and blockchains. What you will learn Understand the role and scope of architecting a successful IoT deployment, from sensors to the cloud Scan the landscape of IoT technologies that span everything from sensors to the cloud and everything in between See the trade-offs in choices of protocols and communications in IoT deployments Build a repertoire of skills and the vernacular necessary to work in the IoT space Broaden your skills in multiple engineering domains necessary for the IoT architect Who this book is for This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, various technologies, and tradeoffs and develop a 50,000-foot view of IoT architecture.

Download or read book Advances in Evolutionary Computing written by Ashish Ghosh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.

Download or read book Information Technologies in Medicine written by Ewa Piętka and published by Springer. This book was released on 2016-05-27 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: ITiB’2016 is the 5th Conference on Information Technologies in Biomedicine organized by the Department of Informatics & Medical Equipment of Silesian University of Technology every other year. The Conference is under the auspices of the Committee on Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. The meeting has become a recognized event that helps to bridge the gap between methodological achievements in engineering and clinical requirements in medical diagnosis, therapy, and rehabilitation. Mathematical information analysis, computer applications together with medical equipment and instruments have become standard tools underpinning the current rapid progress with developing Computational Intelligence. Members of academic societies of technical and medical background present their research results and clinical implementations. This proceedings (divided in 2 volumes) include the following sections: ؠ Image Processing ؠ Signal Processing ؠ Medical Information System & Database ؠ Ambient Assisted Living ؠ Bioinformatics ؠ Modeling & Simulation ؠ Biomechatronics ؠ Biomaterials