Neural Network Learning and Expert Systems

MIT Press

Neural Network Learning and Expert Systems is the
first book to present a unified and in-depth development of neural network learning
algorithms and neural network expert systems. Especially suitable for students and
researchers in computer science, engineering, and psychology, this text and
reference provides a systematic development of neural network learning algorithms
from a computational perspective, coupled with an extensive exploration of neural
network expert systems which shows how the power of neural network learning can be
harnessed to generate expert systems automatically.

Features
include a comprehensive treatment of the standard learning algorithms (with many
proofs), along with much original research on algorithms and expert systems.
Additional chapters explore constructive algorithms, introduce computational
learning theory, and focus on expert system applications to noisy and redundant
problems.

For students there is a large collection of exercises,
as well as a series of programming projects that lead to an extensive neural network
software package. All of the neural network models examined can be implemented using
standard programming languages on a microcomputer.

Autoren/Hrsg.

Gallant, Stephen I.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Über Autor(innen)

Gallant, Stephen I.
Stephen l. Gallant taught courses in neural network learning and expert systems as
Associate Professor of Computer Science at Northeastern University. He is currently
a Senior Scientist at HNC, Inc.