Abstract

One of the main obstacles to reliable communications is the inter symbol interference. An adaptive equalizer is required at the receiver to mitigate the effects of non-ideal channel characteristics and to obtain reliable data transmission. The conventional way to combat with ISI is to include an equalizer in the receiver. This paper presents a new approach to equalization of communication channels using Functional Link Artificial Neural Networks (FLANNs). A novel method of training the FLANNs using PSO Algorithm is described. The performance of the proposed network has been compared with the conventional LMS based channel equalizer and FLANN trained with BP algorithm based equalizer. From the results it can be noted that the proposed algorithm improves the classification capability of the FLANNs in differentiating the received data.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.