Abstract
In order to reduce the complexity and enhance the performance of the Bayesian equalizer (REQ) using the radial basis function (RBF) network, a new equalizer (RNEQ) using the RBF network with a nonlinear multilayer combiner is proposed. The proposed RNEQ produces the output using nonlinear multilayer combiner. The RNEQ is applied to a digital communication system and a nonlinear magnetic storage system. From computer simulation results, the RNEQ with almost 70% reduced structure over the REQ shows nearly the same performance in a digital communication system. And in a nonlinear digital storage system the RNEQ is superior to the REQ. In addition, the RNEQ converges to lower mean squared error value than the other equalizers.
| Original language | English |
|---|---|
| Pages | 353-362 |
| Number of pages | 10 |
| Publication status | Published - 1999 Dec 1 |
| Event | Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) - Madison, WI, USA Duration: 1999 Aug 23 → 1999 Aug 25 |
Other
| Other | Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) |
|---|---|
| City | Madison, WI, USA |
| Period | 99/8/23 → 99/8/25 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Signal Processing
- Software
Cite this
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Suboptimal bayesian equalizer using an nonlinear multilayer combiner. / Choi, Sooyong; Hong, Daesik.
1999. 353-362 Paper presented at Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99), Madison, WI, USA, .Research output: Contribution to conference › Paper
TY - CONF
T1 - Suboptimal bayesian equalizer using an nonlinear multilayer combiner
AU - Choi, Sooyong
AU - Hong, Daesik
PY - 1999/12/1
Y1 - 1999/12/1
N2 - In order to reduce the complexity and enhance the performance of the Bayesian equalizer (REQ) using the radial basis function (RBF) network, a new equalizer (RNEQ) using the RBF network with a nonlinear multilayer combiner is proposed. The proposed RNEQ produces the output using nonlinear multilayer combiner. The RNEQ is applied to a digital communication system and a nonlinear magnetic storage system. From computer simulation results, the RNEQ with almost 70% reduced structure over the REQ shows nearly the same performance in a digital communication system. And in a nonlinear digital storage system the RNEQ is superior to the REQ. In addition, the RNEQ converges to lower mean squared error value than the other equalizers.
AB - In order to reduce the complexity and enhance the performance of the Bayesian equalizer (REQ) using the radial basis function (RBF) network, a new equalizer (RNEQ) using the RBF network with a nonlinear multilayer combiner is proposed. The proposed RNEQ produces the output using nonlinear multilayer combiner. The RNEQ is applied to a digital communication system and a nonlinear magnetic storage system. From computer simulation results, the RNEQ with almost 70% reduced structure over the REQ shows nearly the same performance in a digital communication system. And in a nonlinear digital storage system the RNEQ is superior to the REQ. In addition, the RNEQ converges to lower mean squared error value than the other equalizers.
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M3 - Paper
SP - 353
EP - 362
ER -