|
DSpace@nitr >
National Institue of Technology- Rourkela >
Thesis (Doctor of Philosophy) >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/690
|
| Title: | Adaptive Equalisation of Communication Channels Using ANN Techniques |
| Authors: | Das, Susmita
Satapathy, J K (Guide) |
| Keywords: | Adaptive Equalisation
Inter Symbol Interference
Communication Channel
Decision Feedback Equaliser
Nonlinear Equalisers
Feedforward Neural Network |
| Issue Date: | 2004 |
| Publisher: | National Institute of Technology, Rourkela |
| Citation: | Adaptive Equalisation of Communication Channels Using ANN Techniques, Thesis submitted in partial fulfillment of the requirements for the award of the Doctor of Philosophy in Electrical Engineering, Submitted to National Institute of Technology, Rourkela |
| Abstract: | Channel equalisation is a process of compensating the disruptive effects caused
mainly by Inter Symbol Interference in a band-limited channel and plays a vital role for
enabling higher data rate in digital communication. The development of new training
algorithms, structures and the selection of the design parameters for equalisers are active
fields of research which are exploiting the benefits of different signal processing
techniques. Designing efficient equalisers based on low structural complexity, is also an
area of much interest keeping in view of real-time implementation issue. However, it has
been widely reported that optimal performance can only be realised using nonlinear
equalisers. As Artificial Neural Networks are inherently nonlinear processing elements
and possess capabilities of universal approximation and pattern classification, these are well suited for developing high performance adaptive equalisers.
This proposed work has significantly contributed to the d... |
| Description: | Copyright for the thesis belongs to National Institute of Technology Rourkela |
| URI: | http://hdl.handle.net/2080/690 |
| Appears in Collections: | Thesis (Doctor of Philosophy)
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| Final-thesis-susmita dada.pdf | | 5335Kb | Adobe PDF | View/Open |
|
Show full item record
All items in DSpace are protected by copyright, with all rights reserved.
|
