The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions

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dc.contributor.advisorGreene, Johnen_ZA
dc.contributor.authorOlshewsky, Avron Bernarden_ZA
dc.date.accessioned2014-11-10T08:54:54Z
dc.date.available2014-11-10T08:54:54Z
dc.date.issued1997en_ZA
dc.descriptionBibliography: leaves. 63-66.en_ZA
dc.description.abstractNeural networks have been applied to a number of problems over the past few years. One of the emerging applications of neural networks is adaptive communication channel equalisation. This area of research has become prominent due to the reformulation of the equalisation problem as a classification problem. Viewing equalisation as a classification problem allows researchers to apply the knowledge gained from other fields to equalisation. A wide variety of neural network structures have been suggested to equalise communication channels. Each structure may in turn have a number of different possible algorithms to train the equaliser. A neural network is essentially a non-linear classifier; in general a neural network is able to classify data by employing a non-linear function. The primary subject of this dissertation is the comparative performance of neural networks employing non-localised basis (non-linear) functions (Multi-layer Perceptron) versus those employing localised basis functions (Radial Basis Function Network).en_ZA
dc.identifier.apacitationOlshewsky, A. B. (1997). <i>The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/9472en_ZA
dc.identifier.chicagocitationOlshewsky, Avron Bernard. <i>"The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 1997. http://hdl.handle.net/11427/9472en_ZA
dc.identifier.citationOlshewsky, A. 1997. The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Olshewsky, Avron Bernard AB - Neural networks have been applied to a number of problems over the past few years. One of the emerging applications of neural networks is adaptive communication channel equalisation. This area of research has become prominent due to the reformulation of the equalisation problem as a classification problem. Viewing equalisation as a classification problem allows researchers to apply the knowledge gained from other fields to equalisation. A wide variety of neural network structures have been suggested to equalise communication channels. Each structure may in turn have a number of different possible algorithms to train the equaliser. A neural network is essentially a non-linear classifier; in general a neural network is able to classify data by employing a non-linear function. The primary subject of this dissertation is the comparative performance of neural networks employing non-localised basis (non-linear) functions (Multi-layer Perceptron) versus those employing localised basis functions (Radial Basis Function Network). DA - 1997 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1997 T1 - The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions TI - The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions UR - http://hdl.handle.net/11427/9472 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/9472
dc.identifier.vancouvercitationOlshewsky AB. The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 1997 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/9472en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleThe application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functionsen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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