Digital Filter Design Using Artificial Neural Network.
| dc.contributor.author | Adewole, A.P. | |
| dc.contributor.author | Agwuegbo, S.O. | |
| dc.date.accessioned | 2019-09-10T10:49:42Z | |
| dc.date.available | 2019-09-10T10:49:42Z | |
| dc.date.issued | 2010-06 | |
| dc.description | Staff publications | en_US |
| dc.description.abstract | In this paper, Feed Forward Multi-Layer Perceptron neural network was adapted as a digital filtering tool in modelling communications systems that were corrupted by noise or interference. Discrete-Fourier Transform was used to reduce error in transmission. The input and target output data from the study were generated using ionosphere data radar, and this proved to be essential and necessary for training and testing the network. The network was trained using MATLAB R2008a and the training resulted to the minimisation of the error. The result of digit filtration shows a near error-free output. In conclusion, the forward-feed multilayered neural network can be used to build a functional digital filter. | en_US |
| dc.identifier.citation | Adewole, A.P., and Agwuegbo, S.O. (2010). Digital Filter Design Using Artificial Neural Network. Journal of Computer Science and its Applications, Vol.17 (1). | en_US |
| dc.identifier.uri | https://ir.unilag.edu.ng/handle/123456789/5457 | |
| dc.language.iso | en | en_US |
| dc.publisher | Journal of Computer Science and its Applications | en_US |
| dc.relation.ispartofseries | Journal of Computer Science and its Applications;Vol.17(1) | |
| dc.subject | Analog Signal | en_US |
| dc.subject | Data Communication | en_US |
| dc.subject | Digital Signal | en_US |
| dc.subject | Neural Networks | en_US |
| dc.subject | Signal Processing | en_US |
| dc.subject | Research Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer science | en_US |
| dc.title | Digital Filter Design Using Artificial Neural Network. | en_US |
| dc.type | Article | en_US |