Search for dissertations about: "Anders Lansner"
Showing result 11 - 15 of 22 swedish dissertations containing the words Anders Lansner.
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11. Modeling prediction and pattern recognition in the early visual and olfactory systems
Abstract : Our senses are our mind's window to the outside world and determine how we perceive our environment.Sensory systems are complex multi-level systems that have to solve a multitude of tasks that allow us to understand our surroundings. READ MORE
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12. Oscillations and spike statistics in biophysical attractor networks
Abstract : The work of this thesis concerns how cortical memories are stored and retrieved. In particular, large-scale simulations are used to investigate the extent to which associative attractor theory is compliant with known physiology and in vivo dynamics. READ MORE
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13. Sequence learning in the Bayesian Confidence Propagation Neural Network
Abstract : This thesis examines sequence learning in the Bayesian Confidence PropagationNeural Network (BCPNN). The methodology utilized throughout this work is com-putational and analytical in nature and the contributions here presented can beunderstood along the following four major themes: 1) this work starts by revisitingthe properties of the BCPNN as an attractor neural network and then provides anovel formalization of some of those properties. READ MORE
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14. Aspects of memory and representation in cortical computation
Abstract : Denna avhandling i datalogi föreslår modeller för hur vissa beräkningsmässiga uppgifter kan utföras av hjärnbarken. Utgångspunkten är dels kända fakta om hur en area i hjärnbarken är uppbyggd och fungerar, dels etablerade modellklasser inom beräkningsneurobiologi, såsom attraktorminnen och system för gles kodning. READ MORE
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15. Some computational aspects of attractor memory
Abstract : In this thesis I present novel mechanisms for certain computational capabilities of the cerebral cortex, building on the established notion of attractor memory. A sparse binary coding network for generating efficient representation of sensory input is presented. READ MORE