A weighted voting model of associative memory. 2007

Xiaoyan Mu, and Paul Watta, and Mohamad H Hassoun
Department of Electrical and Computer Engineering, Rose-Hulman Institute of Technology, Terre Haute, IN 47803, USA. mu@Rose-Hulman.edu

This paper presents an analysis of a random access memory (RAM)-based associative memory which uses a weighted voting scheme for information retrieval. This weighted voting memory can operate in heteroassociative or autoassociative mode, can store both real-valued and binary-valued patterns and, unlike memory models, is equipped with a rejection mechanism. A theoretical analysis of the performance of the weighted voting memory is given for the case of binary and random memory sets. Performance measures are derived as a function of the model parameters: pattern size, window size, and number of patterns in the memory set. It is shown that the weighted voting model has large capacity and error correction. The results show that the weighted voting model can successfully achieve high-detection and -identification rates and, simultaneously, low-false-acceptance rates.

UI MeSH Term Description Entries
D008568 Memory Complex mental function having four distinct phases: (1) memorizing or learning, (2) retention, (3) recall, and (4) recognition. Clinically, it is usually subdivided into immediate, recent, and remote memory.
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
D010363 Pattern Recognition, Automated In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed) Automated Pattern Recognition,Pattern Recognition System,Pattern Recognition Systems
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D003661 Decision Support Techniques Mathematical or statistical procedures used as aids in making a decision. They are frequently used in medical decision-making. Decision Analysis,Decision Modeling,Models, Decision Support,Analysis, Decision,Decision Aids,Decision Support Technics,Aid, Decision,Aids, Decision,Analyses, Decision,Decision Aid,Decision Analyses,Decision Support Model,Decision Support Models,Decision Support Technic,Decision Support Technique,Model, Decision Support,Modeling, Decision,Technic, Decision Support,Technics, Decision Support,Technique, Decision Support,Techniques, Decision Support
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D001185 Artificial Intelligence Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language. AI (Artificial Intelligence),Computer Reasoning,Computer Vision Systems,Knowledge Acquisition (Computer),Knowledge Representation (Computer),Machine Intelligence,Computational Intelligence,Acquisition, Knowledge (Computer),Computer Vision System,Intelligence, Artificial,Intelligence, Computational,Intelligence, Machine,Knowledge Representations (Computer),Reasoning, Computer,Representation, Knowledge (Computer),System, Computer Vision,Systems, Computer Vision,Vision System, Computer,Vision Systems, Computer
D016247 Information Storage and Retrieval Organized activities related to the storage, location, search, and retrieval of information. Information Retrieval,Data Files,Data Linkage,Data Retrieval,Data Storage,Data Storage and Retrieval,Information Extraction,Information Storage,Machine-Readable Data Files,Data File,Data File, Machine-Readable,Data Files, Machine-Readable,Extraction, Information,Files, Machine-Readable Data,Information Extractions,Machine Readable Data Files,Machine-Readable Data File,Retrieval, Data,Storage, Data
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
D032701 Biomimetics An interdisciplinary field in materials science, ENGINEERING, and BIOLOGY, studying the use of biological principles for synthesis or fabrication of BIOMIMETIC MATERIALS. Mimetics, Biological,Bio-inspired Engineering,Biomimicry Engineering,Biomimicry Science,Bio inspired Engineering,Bio-inspired Engineerings,Biological Mimetic,Biological Mimetics,Biomimetic,Biomimicry Engineerings,Biomimicry Sciences,Engineering, Bio-inspired,Engineering, Biomimicry,Engineerings, Bio-inspired,Engineerings, Biomimicry,Mimetic, Biological,Science, Biomimicry,Sciences, Biomimicry

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