Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how fast the computation time and number of neurons grow as the...

Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through...

This popular introductory linguistics text is unique in the way various themes are integrated throughout the book. One primary theme is the question, "How is a speaker's communicative intent recognized?" Rather than treat phonology, phonetics, morphology, syntax, semantics, and pragmatics as completely separate fields, the text...

The classical view of concepts in psychology was challenged in the 1970s when experimental evidence showed that concept categories are graded and thus cannot be represented adequately by classical sets. The possibility of using fuzzy set theory and fuzzy logic for representing and dealing with concepts was recognized initially but then...

This text offers a comprehensive treatment of VHDL and its applications to the design and simulation of real, industry-standard circuits. It focuses on the use of VHDL rather than solely on the language, showing why and how certain types of circuits are inferred from the language constructs and how any of the four simulation categories can be...

What matters in understanding digital media? Is looking at the external appearance and audience experience of software enough--or should we look further? In Expressive Processing, Noah Wardrip-Fruin argues that understanding what goes on beneath the surface, the computational processes that make digital media function, is...

The gradual disappearance of paper and its familiar evidential qualities affects almost every dimension of contemporary life. From health records to ballots, almost all documents are now digitized at some point of their life cycle, easily copied, altered, and distributed. In Burdens of Proof, Jean-François Blanchette examines...

Over a century ago, William James proposed that people search through memory much as they rummage through a house looking for lost keys. We scour our environments for territory, food, mates, and information. We search for items in visual scenes, for historical facts, and for the best deals on Internet sites; we search for new friends to add...

Computing isn't simply about hardware or software, or calculation or applications. Computing, writes Paul Rosenbloom, is an exciting and diverse, yet remarkably coherent, scientific enterprise that is highly multidisciplinary yet maintains a unique core of its own. In On Computing, Rosenbloom proposes that computing is a great...

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier.

Judd looks beyond the scope...

Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves...