Paul John Werbos's Books

The Roots of Backpropagation

From Ordered Derivatives to Neural Networks and Political Forecasting

By: Paul John Werbos

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The Roots of Backpropagation

From Ordered Derivatives to Neural Networks and Political Forecasting

By: Paul John Werbos

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

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Page Count

340

Publisher

John Wiley & Sons

Published Date

ISBN 10

0471598976

ISBN 13

9780471598978

The Roots of Backpropagation

From Ordered Derivatives to Neural Networks and Political Forecasting

By: Paul John Werbos

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The Roots of Backpropagation

From Ordered Derivatives to Neural Networks and Political Forecasting

By: Paul John Werbos

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N/A

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Solve jigsaw puzzle

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Page Count

340

Publisher

John Wiley & Sons

Published Date

ISBN 10

0471598976

ISBN 13

9780471598978

Neural Networks in Finance

Gaining Predictive Edge in the Market

By: Paul D. McNelis

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Neural Networks in Finance

Gaining Predictive Edge in the Market

By: Paul D. McNelis

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

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Page Count

262

Publisher

Academic Press

Published Date

ISBN 10

0124859674

ISBN 13

9780124859678

Artificial Neural Networks

An Introduction

By: Kevin L. Priddy,Paul E. Keller

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Artificial Neural Networks

An Introduction

By: Kevin L. Priddy,Paul E. Keller

This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.

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Page Count

184

Publisher

SPIE Press

Published Date

ISBN 10

0819459879

ISBN 13

9780819459879

Principles of Neural Model Identification, Selection and Adequacy

With Applications to Financial Econometrics

By: Achilleas Zapranis,Apostolos-Paul N. Refenes

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Principles of Neural Model Identification, Selection and Adequacy

With Applications to Financial Econometrics

By: Achilleas Zapranis,Apostolos-Paul N. Refenes

Neural networks have had considerable success in a variety of disciplines including engineering, control, and financial modelling. However a major weakness is the lack of established procedures for testing mis-specified models and the statistical significance of the various parameters which have been estimated. This is particularly important in the majority of financial applications where the data generating processes are dominantly stochastic and only partially deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the theoretical framework required, and displays the efficient use of neural networks for modelling complex financial phenomena. Unlike most other books in this area, this one treats neural networks as statistical devices for non-linear, non-parametric regression analysis.

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Page Count

194

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1447105591

ISBN 13

9781447105596

Book's by Paul John Werbos

The Roots of Backpropagation

The Roots of Backpropagation

The Roots of Backpropagation

The Roots of Backpropagation

Neural Networks in Finance

Neural Networks in Finance

Artificial Neural Networks

Artificial Neural Networks

Principles of Neural Model Identification, Selection and Adequacy

Principles of Neural Model Identification, Selection and Adequacy

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