1_Intro.pdf - Objectives 1 1 Introduction Objectives History Applications Biological Inspiration Further Reading 1-1 1-2 1-5 1-8 1-10 Objectives As you

1_Intro.pdf - Objectives 1 1 Introduction Objectives...

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1-1 1 1 Introduction Objectives 1-1 History 1-2 Applications 1-5 Biological Inspiration 1-8 Further Reading 1-10 Objectives As you read these words you are using a complex biological neural network. You have a highly interconnected set of some 10 11 neurons to facilitate your reading, breathing, motion and thinking. Each of your biological neurons, a rich assembly of tissue and chemistry, has the complexity, if not the speed, of a microprocessor. Some of your neural structure was with you at birth. Other parts have been established by experience. Scientists have only just begun to understand how biological neural net- works operate. It is generally understood that all biological neural func- tions, including memory, are stored in the neurons and in the connections between them. Learning is viewed as the establishment of new connections between neurons or the modification of existing connections. This leads to the following question: Although we have only a rudimentary understand- ing of biological neural networks, is it possible to construct a small set of simple artificial °neurons± and perhaps train them to serve a useful func- tion? The answer is °yes.± This book, then, is about artificial neural net- works. The neurons that we consider here are not biological. They are extremely simple abstractions of biological neurons, realized as elements in a pro- gram or perhaps as circuits made of silicon. Networks of these artificial neurons do not have a fraction of the power of the human brain, but they can be trained to perform useful functions. This book is about such neu- rons, the networks that contain them and their training.
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1 Introduction 1-2 History The history of artificial neural networks is filled with colorful, creative in- dividuals from many different fields, many of whom struggled for decades to develop concepts that we now take for granted. This history has been documented by various authors. One particularly interesting book is Neu- rocomputing: Foundations of Research by John Anderson and Edward Rosenfeld. They have collected and edited a set of some 43 papers of special historical interest. Each paper is preceded by an introduction that puts the paper in historical perspective. Histories of some of the main neural network contributors are included at the beginning of various chapters throughout this text and will not be re- peated here. However, it seems appropriate to give a brief overview, a sam- ple of the major developments. At least two ingredients are necessary for the advancement of a technology: concept and implementation. First, one must have a concept, a way of thinking about a topic, some view of it that gives a clarity not there before. This may involve a simple idea, or it may be more specific and include a mathematical description. To illustrate this point, consider the history of the heart. It was thought to be, at various times, the center of the soul or a source of heat. In the 17th century medical practitioners finally began to
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  • Summer '18
  • Shiv
  • Artificial neural network, neural network

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