Download or read book Feed Forward written by Mark B. N. Hansen and published by University of Chicago Press. This book was released on 2015-01-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Even as media in myriad forms increasingly saturate our lives, we nonetheless tend to describe our relationship to it in terms from the twentieth century: we are consumers of media, choosing to engage with it. In Feed-Forward, Mark B. N. Hansen shows just how outmoded that way of thinking is: media is no longer separate from us but has become an inescapable part of our very experience of the world. Drawing on the speculative empiricism of philosopher Alfred North Whitehead, Hansen reveals how new media call into play elements of sensibility that greatly affect human selfhood without in any way belonging to the human. From social media to data-mining to new sensor technologies, media in the twenty-first century work largely outside the realm of perceptual consciousness, yet at the same time inflect our every sensation. Understanding that paradox, Hansen shows, offers us a chance to put forward a radically new vision of human becoming, one that enables us to reground the human in a non-anthropocentric view of the world and our experience in it.

Download or read book Neural Smithing written by Russell Reed and published by MIT Press. This book was released on 1999-02-17 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition). This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.

Download or read book Feed Forward Neural Networks written by Jouke Annema and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses.

Download or read book Feedback to Feed Forward written by Amy Tepper and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feedback that works - for leadership that makes a difference. Leaders know that feedback is essential to teacher development. Crafting the right feedback, however, can be daunting. This how-to book introduces a dynamic-yet-practical leadership model that helps leaders in all roles and at all experience levels conduct comprehensive observations, analyze lessons for effectiveness, and develop high-leverage action steps that change practices and outcomes.

Download or read book The Feedback Fix written by Joe Hirsch and published by Rowman & Littlefield. This book was released on 2017-04-18 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highly recommended by bestselling author Marshall Goldsmith The secret to giving better feedback isn’t what we say – it’s what others hear. Too often, people hear about a past they can’t control, not a future they can. That changes with “feedforward” – a radical approach to sharing feedback that unleashes the performance and potential of everyone around us. From managers and coaches trying to energize their teams, to teachers hoping to motivate their students, to parents looking to empower their children, people from all walks of life want others to hear what they have to say. Through a lively blend of stories and studies, The Feedback Fix shows them how by presenting a six-part REPAIR plan that spreads feedforward across boardrooms, classrooms, and even dining rooms. Even with drastic changes in how we work and live, the experiences we create for others – joy or fear, growth or decline, success or failure – still hang on the feedback we share. The Feedback Fix makes a compelling argument for getting what we want by giving others what they need – all while rebuilding the way we lead, learn, and live.

Download or read book Feedback to Feed Forward written by Amy Tepper and published by Corwin Press. This book was released on 2018-06-13 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feedback that works—for leadership that makes a difference. Leaders know that feedback is essential to teacher development. Crafting the right feedback, however, can be daunting. This how-to book introduces a dynamic yet practical leadership model that helps leaders in all roles and at all experience levels conduct comprehensive observations, analyze lessons for effectiveness, and develop high-leverage action steps that change practices and outcomes. Features include Comprehensive explanations of standards and discrete core skills Explicit think-alouds, ready-to-use strategies, and field-tested lesson examples Evidence-collection notes—with templates—from live observations Feedback samples across grade levels and content areas Reblicable case studies for professional learning

Download or read book Feedforward and Feedback Processes in Vision written by Hulusi Kafaligonul and published by Frontiers Media SA. This book was released on 2015-07-10 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visual system consists of hierarchically organized distinct anatomical areas functionally specialized for processing different aspects of a visual object (Felleman & Van Essen, 1991). These visual areas are interconnected through ascending feedforward projections, descending feedback projections, and projections from neural structures at the same hierarchical level (Lamme et al., 1998). Accumulating evidence from anatomical, functional and theoretical studies suggests that these three projections play fundamentally different roles in perception. However, their distinct functional roles in visual processing are still subject to debate (Lamme & Roelfsema, 2000). The focus of this Research Topic is the roles of feedforward and feedback projections in vision. Even though the notions of feedforward, feedback, and reentrant processing are widely accepted, it has been found difficult to distinguish their individual roles on the basis of a single criterion. We welcome empirical contributions, theoretical contributions and reviews that fit into any one (or a combination) of the following domains: 1) their functional roles for perception of specific features of a visual object 2) their contributions to the distinct modes of visual processing (e.g., pre-attentive vs. attentive, conscious vs. unconscious) 3) recent techniques/methodologies to identify distinct functional roles of feedforward and feedback projections and corresponding neural signatures. We believe that the current Research Topic will not only provide recent information about feedforward/feedback processes in vision but also contribute to the understanding fundamental principles of cortical processing in general.

Download or read book Feedforward Neural Network Methodology written by Terrence L. Fine and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This decade has seen an explosive growth in computational speed and memory and a rapid enrichment in our understanding of artificial neural networks. These two factors provide systems engineers and statisticians with the ability to build models of physical, economic, and information-based time series and signals. This book provides a thorough and coherent introduction to the mathematical properties of feedforward neural networks and to the intensive methodology which has enabled their highly successful application to complex problems.

Download or read book Control Theoretic Models of Feedforward in Manual Control written by Frank M. Drop and published by Logos Verlag Berlin GmbH. This book was released on 2016-11-03 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding how humans control a vehicle (cars, aircraft, bicycles, etc.) enables engineers to design faster, safer, more comfortable, more energy efficient, more versatile, and thus better vehicles. In a typical control task, the Human Controller (HC) gives control inputs to a vehicle such that it follows a particular reference path (e.g., the road) accurately. The HC is simultaneously required to attenuate the effect of disturbances (e.g., turbulence) perturbing the intended path of the vehicle. To do so, the HC can use a control organization that resembles a closed-loop feedback controller, a feedforward controller, or a combination of both. Previous research has shown that a purely closed-loop feedback control organization is observed only in specific control tasks, that do not resemble realistic control tasks, in which the information presented to the human is very limited. In realistic tasks, a feedforward control strategy is to be expected; yet, almost all previously available HC models describe the human as a pure feedback controller lacking the important feedforward response. Therefore, the goal of the research described in this thesis was to obtain a fundamental understanding of feedforward in human manual control. First, a novel system identification method was developed, which was necessary to identify human control dynamics in control tasks involving realistic reference signals. Second, the novel identification method was used to investigate three important aspects of feedforward through human-in-the-loop experiments which resulted in a control-theoretical model of feedforward in manual control. The central element of the feedforward model is the inverse of the vehicle dynamics, equal to the theoretically ideal feedforward dynamics. However, it was also found that the HC is not able to apply a feedforward response with these ideal dynamics, and that limitations in the perception, cognition, and action loop need to be modeled by additional model elements: a gain, a time delay, and a low-pass filter. Overall, the thesis demonstrated that feedforward is indeed an essential part of human manual control behavior and should be accounted for in many human-machine applications.

Download or read book Natural Language Processing with PyTorch written by Delip Rao and published by O'Reilly Media. This book was released on 2019-01-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Download or read book Neuro motor control and feed forward models of locomotion in humans written by Marco Iosa and published by Frontiers Media SA. This book was released on 2015-07-29 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Locomotion involves many different muscles and the need of controlling several degrees of freedom. Despite the Central Nervous System can finely control the contraction of individual muscles, emerging evidences indicate that strategies for the reduction of the complexity of movement and for compensating the sensorimotor delays may be adopted. Experimental evidences in animal and lately human model led to the concept of a central pattern generator (CPG) which suggests that circuitry within the distal part of CNS, i.e. spinal cord, can generate the basic locomotor patterns, even in the absence of sensory information. Different studies pointed out the role of CPG in the control of locomotion as well as others investigated the neuroplasticity of CPG allowing for gait recovery after spinal cord lesion. Literature was also focused on muscle synergies, i.e. the combination of (locomotor) functional modules, implemented in neuronal networks of the spinal cord, generating specific motor output by imposing a specific timing structure and appropriate weightings to muscle activations. Despite the great interest that this approach generated in the last years in the Scientific Community, large areas of investigations remain available for further improvement (e.g. the influence of afferent feedback and environmental constrains) for both experimental and simulated models. However, also supraspinal structures are involved during locomotion, and it has been shown that they are responsible for initiating and modifying the features of this basic rhythm, for stabilising the upright walking, and for coordinating movements in a dynamic changing environment. Furthermore, specific damages into spinal and supraspinal structures result in specific alterations of human locomotion, as evident in subjects with brain injuries such as stroke, brain trauma, or people with cerebral palsy, in people with death of dopaminergic neurons in the substantia nigra due to Parkinson’s disease, or in subjects with cerebellar dysfunctions, such as patients with ataxia. The role of cerebellum during locomotion has been shown to be related to coordination and adaptation of movements. Cerebellum is the structure of CNS where are conceivably located the internal models, that are neural representations miming meaningful aspects of our body, such as input/output characteristics of sensorimotor system. Internal model control has been shown to be at the basis of motor strategies for compensating delays or lacks in sensorimotor feedbacks, and some aspects of locomotion need predictive internal control, especially for improving gait dynamic stability, for avoiding obstacles or when sensory feedback is altered or lacking. Furthermore, despite internal model concepts are widespread in neuroscience and neurocognitive science, neurorehabilitation paid far too little attention to the potential role of internal model control on gait recovery. Many important scientists have contributed to this Research Topic with original studies, computational studies, and review articles focused on neural circuits and internal models involved in the control of human locomotion, aiming at understanding the role played in control of locomotion of different neural circuits located at brain, cerebellum, and spinal cord levels.

Download or read book Control System Design Guide written by George Ellis and published by Elsevier. This book was released on 2004-04-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control System Design Guide, 3E will help engineers to apply control theory to practical systems using their PC. This book provides an intuitive approach to controls, avoiding unnecessary mathematics and emphasizing key concepts with more than a dozen control system models. Whether readers are just starting to use controllers or have years of experience, this book will help them improve their machines and processes. - Teaches controls with an intuitive approach, avoiding unnecessary mathematics - Key topics are demonstrated with realistic models of control systems - All models written in Visual ModelQ, a full graphical simulation environment available freely via the internet - New material on OBSERVERS explained using practical applications - Explains how to model machines and processes, including how to measure working equipment; describes many nonlinear behaviours seen in industrial control systems - Electronic motion control, including details of how motors and motor feedback devices work, causes and cures of mechanical resonance, and how position loops work

Download or read book Deep Learning By Example written by Ahmed Menshawy and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book Description Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is for This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.

Download or read book Neural Networks with R written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-09-27 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.

Download or read book Design and Evaluation of a Stochastic Optimal Feed forward and Feedback Technology SOFFT Flight Control Architecture written by Aaron J. Ostroff and published by . This book was released on 1994 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Feedforward Control written by José Luis Guzmán and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-07-01 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there are thousands of books written about feedback control, it is surprising that this is the very first book about feedforward control. Feedforward control is a very powerful technique to compensate for measurable load disturbances in regulation control problems, and the use of feedforward control to assist the traditional feedback controllers is rapidly increasing in industry. The main goal of this book is to describe the power of feedforward control and to present different tuning rules for these controllers. To achieve this goal, theoretical and practical contributions are presented throughout the book to make the technique understandable and easy to implement. The book contains many practical aspects, both in terms of tuning and implementation of the feedforward controller. Many simulation examples are also provided, as well as a presentation of industrial experiences obtained from feedforward control applied to temperature control in greenhouses. For these reasons, we believe that the book will be useful not only at various levels in the teaching systems, but also for engineers working in industry.

Download or read book Data Mining Southeast Asia Edition written by Jiawei Han and published by Elsevier. This book was released on 2006-04-06 with total page 772 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. - A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data - Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning - Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects - Complete classroom support for instructors at www.mkp.com/datamining2e companion site