Biomaterial Database

A multifactor winner-take-all dynamics. 2011

Junmei Zhu

Frankfurt Institute for Advanced Studies, 60438 Frankfurt am Main, Germany. jzhu@fias.uni-frankfurt.de

Perceptual systems often have to disentangle different factors from mixed observations. If each factor is represented by a set of variables, each standing for a discrete value of the factor, the factor values underlying an observation can be extracted by a winner-take-all (WTA) mechanism over the direct product of the factors. Search in the product space, however, is expensive. It is computationally attractive to work on the marginal factors. In this letter we study the dynamics of a multifactor system modeled by a number of interacting WTA dynamics, one for each factor. We give theoretical results on the stable fixed points of this system and show experimental results on invariant object recognition.

UI	MeSH Term	Description	Entries
D008962	Models, Theoretical	Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.	Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D010775	Photic Stimulation	Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity.	Stimulation, Photic,Visual Stimulation,Photic Stimulations,Stimulation, Visual,Stimulations, Photic,Stimulations, Visual,Visual Stimulations
D003657	Decision Making	The process of making a selective intellectual judgment when presented with several complex alternatives consisting of several variables, and usually defining a course of action or an idea.	Credit Assignment,Assignment, Credit,Assignments, Credit,Credit Assignments
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D021641	Recognition, Psychology	The knowledge or perception that someone or something present has been previously encountered.	Familiarity,Psychological Recognition,Recognition (Psychology),Psychology Recognition,Recognition, Psychological