"A Bradford book."In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its info…
"This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman ani…
"A Bradford book."The use of computers to understand words continues to be an area of burgeoning research. Electric Words is the first general survey of and introduction to the entire range of work in lexical linguistics and corpora -- the study of such on-line resources as dictionaries and other texts -- in the broader fields of natural-language processing and artificial intelligence. The auth…
A mathematical framework that describes learning of invariant representations in the ventral stream, offering both theoretical development and applications.The ventral visual stream is believed to underlie object recognition in primates. Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, …
In this work, Marcin Milkowski argues that the mind can be explained computationally because it is itself computational - whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music.OCLC-licensed vendor bibliographic record.
"A Bradford book.""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 of any one particular learning rule, at a level abo…
How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications.Over the past sixty years, powerful methods of model-based control engineering have been responsible for such dramatic advances in engineering systems as autolanding aircraft, autonomous vehicles, and even weather forecasting. Over those s…
This is a guide to computational modelling methods in neuroscience covering a range of modelling scales from molecular reactions to large neural networks.
The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoining Grammar (TAG), Combinatory Categorical Grammar (CCG), Head-driven Phrase Structure Grammar (HPSG), and Lexical Functional Grammar (LFG). Grammars in these frameworks typically associate linguistically motivated rich descriptions (Supertags) with word…
A Bradford book.""This book has its origins in a meeting, entitled "Toward replacement parts for the brain: intracranial implantations of hardward models of neural circuitry" that took place in Washington, D.C. in August 1989"--Preface.The continuing development of implantable neural prostheses signals a new era in bioengineering and neuroscience research. This collection of essays outlines cur…