The Discrete Leaky Integrate-and-fire Neuron Model Applied to Visual Tracking and Pattern Recognition

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dc.contributor.advisorKaikhah, Khosrow
dc.contributor.authorRisinger, Lon W.
dc.date.accessioned2020-08-24T15:02:18Z
dc.date.available2020-08-24T15:02:18Z
dc.date.issued2004-12
dc.description.abstractThe Discrete Leaky Integrate-and-Fire (DLIF) neuron uses a simple discrete LIF neuron model that is capable of diverse spatio-temporal behavior. We explore the behavior of the DLIF when driven by periodic (coherent) and constant (incoherent) input. Results show that the DLIF is capable of oscillatory behavior, amplitude to phase conversion, holographic paging, and spike coincidence detection. Exploiting temporal aspect of the DLIF neuron, a network of DLIF neurons is constructed which is capable of motion detection, object tracking i.e. pursuit motion, and behavior similar to micro-saccadic behavior exhibited by humans. Additionally, a network of DLIF neurons is constructed which is capable of pattern recognition utilizing an action potential computation technique based on relative firing times of neurons. A novel learning technique is presented which allows selective hebbian learning in time delayed connections in a feedforward network by manipulating the DLIF leak rate during training.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent191 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationRisinger, L. W. (2004). The discrete leaky integrate-and-fire neuron model applied to visual tracking and pattern recognition (Unpublished thesis). Texas State University-San Marcos, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/12457
dc.language.isoen
dc.subjectneural networks
dc.subjectpattern recognition
dc.subjectvisual tracking
dc.titleThe Discrete Leaky Integrate-and-fire Neuron Model Applied to Visual Tracking and Pattern Recognition
dc.typeThesis
thesis.degree.departmentComputer Science
thesis.degree.grantorTexas State University-San Marcos
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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