Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
An Introduction to Neural Networks

Buy
An Introduction to Neural Networks, 9781857286731 (1857286731), CRC Press, 1997
Covers: artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps.

This book grew out of a set of course notes for a neural networks module given as part of a Masters degree in “Intelligent Systems”. The people on this course came from a wide variety of intellectual backgrounds (from philosophy, through psychology to computer science and engineering) and I knew that I could not count on their being able to come to grips with the largely technical and mathematical approach which is often used (and in some ways easier to do). As a result I was forced to look carefully at the basic conceptual principles at work in the subject and try to recast these using ordinary language, drawing on the use of physical metaphors or analogies, and pictorial or graphical representations. I was pleasantly surprised to find that, as a result of this process, my own understanding was considerably deepened; I had now to unravel, as it were, condensed formal descriptions and say exactly how these were related to the “physical” world of artificial neurons, signals, computational processes, etc. However, I was acutely aware that, while a litany of equations does not constitute a full description of fundamental principles, without some mathematics, a purely descriptive account runs the risk of dealing only with approximations and cannot be sharpened up to give any formulaic prescriptions. Therefore, I introduced what I believed was just sufficient mathematics to bring the basic ideas into sharp focus.
(HTML tags aren't allowed.)

Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

From Photon to Pixel: The Digital Camera Handbook (Digital Signal and Image Processing)
From Photon to Pixel: The Digital Camera Handbook (Digital Signal and Image Processing)

This second edition of the fully revised and updated From Photon to Pixel presents essential elements in modern digital photographic devices. Our universal infatuation with photography profoundly affects its usage and development.
While some sides of photographic “culture” remain wholly unchanged – art photography,
...

Circuits, Systems and Signal Processing: A Tutorials Approach
Circuits, Systems and Signal Processing: A Tutorials Approach

This book is a collection of tutorial-like chapters on all core topics of signals and systems and the electronic circuits. All the topics dealt with in the book are parts of the core syllabi of standard programs in Electrical Engineering, Electrical and Computer Engineering, and Electronics and Telecommunication Engineering domains. This book...


Learn Linux in a Month of Lunches
Learn Linux in a Month of Lunches

Summary

Learn Linux in a Month of Lunches shows you how to install and use Linux for all the things you do with your OS, like connecting to a network, installing software, and securing your system. Whether you're just curious about Linux or have to get up and running for your job, you'll appreciate...

Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
With the evolution of our complex technological society and the introduction of new notions and innovative theoretical tools in the field of intelligent systems, the field of neural networks is undergoing an enormous evolution. These evolving and innovative theoretical tools are centered around the theory of soft computing, a theory that embodies...
An Introduction to Numerical Analysis for Electrical and Computer Engineers
An Introduction to Numerical Analysis for Electrical and Computer Engineers
An engineer’s guide to numerical analysis

To properly function in today’s work environment, engineers require a working familiarity with numerical analysis. This book provides that necessary background, striking a balance between analytical rigor and an applied approach focusing on methods particular to the solving of engineering...

©2018 LearnIT (support@pdfchm.net) - Privacy Policy