Deep Learning With Matlab Neural Networks Design And Dynamic Neural Networks

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MATLAB Deep Learning

Author : Phil Kim
Publisher : Apress
ISBN 13 : 1484228456
Total Pages : 162 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis MATLAB Deep Learning by : Phil Kim

Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

Neural Network Design

Author : Martin T. Hagan
Publisher :
ISBN 13 : 9789812403766
Total Pages : pages
Book Rating : 4.4/5 (37 download)

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Book Synopsis Neural Network Design by : Martin T. Hagan

Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

DEEP LEARNING with MATLAB. NEURAL NETWORKS by EXAMPLES

Author : Cesar Perez Lopez
Publisher : CESAR PEREZ
ISBN 13 : 1716584841
Total Pages : 154 pages
Book Rating : 4.7/5 (165 download)

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Book Synopsis DEEP LEARNING with MATLAB. NEURAL NETWORKS by EXAMPLES by : Cesar Perez Lopez

Download or read book DEEP LEARNING with MATLAB. NEURAL NETWORKS by EXAMPLES written by Cesar Perez Lopez and published by CESAR PEREZ. This book was released on 2020-09-13 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB has the tool Deep Learning Toolbox that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets (Big data), you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox.

Deep Neural Networks

Author : Yunong Zhang
Publisher : CRC Press
ISBN 13 : 0429760981
Total Pages : 448 pages
Book Rating : 4.4/5 (297 download)

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Book Synopsis Deep Neural Networks by : Yunong Zhang

Download or read book Deep Neural Networks written by Yunong Zhang and published by CRC Press. This book was released on 2019-03-19 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Toward Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications introduces the outlook and extension toward deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors’ 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet, and allows reader to extend the techniques in the book to solve scientific and engineering problems. The book will be of interest to engineers, senior undergraduates, postgraduates, and researchers in the fields of neuronets, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, simulation and modeling, deep learning, and data mining. Features Focuses on neuronet models, algorithms, and applications Designs, constructs, develops, analyzes, simulates and compares various WASD neuronet models, such as single-input WASD neuronet models, two-input WASD neuronet models, three-input WASD neuronet models, and general multi-input WASD neuronet models for function data approximations Includes real-world applications, such as population prediction Provides complete mathematical foundations, such as Weierstrass approximation, Bernstein polynomial approximation, Taylor polynomial approximation, and multivariate function approximation, exploring the close integration of mathematics (i.e., function approximation theories) and computers (e.g., computer algorithms) Utilizes the authors' 20 years of research on neuronets

Efficient Processing of Deep Neural Networks

Author : Vivienne Sze
Publisher : Springer Nature
ISBN 13 : 3031017668
Total Pages : 254 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze

Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

Static and Dynamic Neural Networks

Author : Madan Gupta
Publisher : John Wiley & Sons
ISBN 13 : 0471460923
Total Pages : 752 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Static and Dynamic Neural Networks by : Madan Gupta

Download or read book Static and Dynamic Neural Networks written by Madan Gupta and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuronale Netze haben sich in vielen Bereichen der Informatik und künstlichen Intelligenz, der Robotik, Prozeßsteuerung und Entscheidungsfindung bewährt. Um solche Netze für immer komplexere Aufgaben entwickeln zu können, benötigen Sie solide Kenntnisse der Theorie statischer und dynamischer neuronaler Netze. Aneignen können Sie sie sich mit diesem Lehrbuch! Alle theoretischen Konzepte sind in anschaulicher Weise mit praktischen Anwendungen verknüpft. Am Ende jedes Kapitels können Sie Ihren Wissensstand anhand von Übungsaufgaben überprüfen.

Data-Driven Science and Engineering

Author : Steven L. Brunton
Publisher : Cambridge University Press
ISBN 13 : 1009098489
Total Pages : 615 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton

Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799804151
Total Pages : 1707 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-10-11 with total page 1707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.

Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition)

Author : Daniel Graupe
Publisher : World Scientific
ISBN 13 : 9811201242
Total Pages : 439 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition) by : Daniel Graupe

Download or read book Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition) written by Daniel Graupe and published by World Scientific. This book was released on 2019-03-15 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained.The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.

Electric Vehicles - Design, Modelling and Simulation

Author : Nicolae Tudoroiu
Publisher : BoD – Books on Demand
ISBN 13 : 1837691770
Total Pages : 172 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Electric Vehicles - Design, Modelling and Simulation by : Nicolae Tudoroiu

Download or read book Electric Vehicles - Design, Modelling and Simulation written by Nicolae Tudoroiu and published by BoD – Books on Demand. This book was released on 2023-12-13 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clean and efficient transportation in countries around the world is only possible if governments and scientists focus on stimulating and supporting the electric vehicle industry by developing and deploying the most advanced Li-ion battery technologies. Recently, several improvements have been made in the direction of operational safety, the elimination of explosion hazards, and the mitigation of chemical toxicity. The state of charge of an electric vehicle battery is an essential internal parameter that plays a vital role in utilizing the battery’s energy efficiency, operating safely in various realistic conditions and environments, and extending the battery’s life. Also, automated systems are integrated into the architecture of electrical vehicles, allowing for technology, machinery, or systems to perform tasks or processes with minimal human intervention. Automation in electric vehicles involves the integration of advanced technologies to enhance the driving experience, improve safety, optimize energy efficiency, and facilitate the transition to sustainable transportation. The key aspects of automation in electric vehicles are advanced driver assistance, self-driving capabilities, battery and energy management, and safety and collision avoidance. This book provides a comprehensive overview of electric and hybrid electric vehicles, exploring their design, the modeling of Li-ion battery management systems, state-of-charge estimation algorithms, and the most used electric motors. It also discusses new trends in electric vehicle automation as well as different control strategies.

Dynamic System Modelling and Analysis with MATLAB and Python

Author : Jongrae Kim
Publisher : John Wiley & Sons
ISBN 13 : 1119801621
Total Pages : 340 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Dynamic System Modelling and Analysis with MATLAB and Python by : Jongrae Kim

Download or read book Dynamic System Modelling and Analysis with MATLAB and Python written by Jongrae Kim and published by John Wiley & Sons. This book was released on 2022-10-18 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic System Modeling & Analysis with MATLAB & Python A robust introduction to the advanced programming techniques and skills needed for control engineering In Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples. The author covers a range of control topics, including attitude dynamics, attitude kinematics, autonomous vehicles, systems biology, optimal estimation, robustness analysis, and stochastic system. An accompanying website includes a solutions manual as well as MATLAB and Python example code. Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers provides readers with a sound starting point to learning programming in the engineering or biology domains. It also offers: A thorough introduction to attitude estimation and control, including attitude kinematics and sensors and extended Kalman filters for attitude estimation Practical discussions of autonomous vehicles mission planning, including unmanned aerial vehicle path planning and moving target tracking Comprehensive explorations of biological network modeling, including bio-molecular networks and stochastic modeling In-depth examinations of control algorithms using biomolecular networks, including implementation Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers is an indispensable resource for advanced undergraduate and graduate students seeking practical programming instruction for dynamic system modeling and analysis using control theory.

Deep Learning Neural Networks: Design And Case Studies

Author : Daniel Graupe
Publisher : World Scientific Publishing Company
ISBN 13 : 9813146478
Total Pages : 280 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Deep Learning Neural Networks: Design And Case Studies by : Daniel Graupe

Download or read book Deep Learning Neural Networks: Design And Case Studies written by Daniel Graupe and published by World Scientific Publishing Company. This book was released on 2016-07-07 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.

Make Your Own Neural Network

Author : Tariq Rashid
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781530826605
Total Pages : 0 pages
Book Rating : 4.8/5 (266 download)

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Book Synopsis Make Your Own Neural Network by : Tariq Rashid

Download or read book Make Your Own Neural Network written by Tariq Rashid and published by Createspace Independent Publishing Platform. This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for anyone who wants to understand what neural network[s] are. It's for anyone who wants to make and use their own. And it's for anyone who wants to appreciate the fairly easy but exciting mathematical ideas that are at the core of how they work. This guide is not aimed at experts in mathematics or computer science. You won't need any special knowledge or mathematical ability beyond school maths [sic] ... Teachers can use this guide as a particularly gentle explanation of neural networks and their implementation to enthuse and excite students making their very own learning artificial intelligence with only a few lines of programming language code. The code has been tested to work with a Raspberry Pi, a small inexpensive computer very popular in schools and with young students"--(page 6, Introduction)

Dynamic Data Assimilation

Author : Dinesh G. Harkut
Publisher : BoD – Books on Demand
ISBN 13 : 1839680830
Total Pages : 120 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Dynamic Data Assimilation by : Dinesh G. Harkut

Download or read book Dynamic Data Assimilation written by Dinesh G. Harkut and published by BoD – Books on Demand. This book was released on 2020-10-28 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.

Knowledge Discovery in the Social Sciences

Author : Xiaoling Shu
Publisher : University of California Press
ISBN 13 : 0520339991
Total Pages : 263 pages
Book Rating : 4.5/5 (23 download)

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Book Synopsis Knowledge Discovery in the Social Sciences by : Xiaoling Shu

Download or read book Knowledge Discovery in the Social Sciences written by Xiaoling Shu and published by University of California Press. This book was released on 2020-02-04 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries

Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes

Author : Krzysztof Patan
Publisher : Springer
ISBN 13 : 3540798722
Total Pages : 223 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes by : Krzysztof Patan

Download or read book Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes written by Krzysztof Patan and published by Springer. This book was released on 2008-06-11 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.

Neural Networks

Author : Gérard Dreyfus
Publisher : Springer Science & Business Media
ISBN 13 : 3540288473
Total Pages : 509 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Neural Networks by : Gérard Dreyfus

Download or read book Neural Networks written by Gérard Dreyfus and published by Springer Science & Business Media. This book was released on 2005-11-25 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts and edited to present a coherent and comprehensive, yet not redundant, practically oriented introduction.