| DC 欄位 |
值 |
語言 |
| DC.contributor | 通訊工程學系 | zh_TW |
| DC.creator | 卓奕璿 | zh_TW |
| DC.creator | Yi-Hsuan Cho | en_US |
| dc.date.accessioned | 2011-7-27T07:39:07Z | |
| dc.date.available | 2011-7-27T07:39:07Z | |
| dc.date.issued | 2011 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=975203026 | |
| dc.contributor.department | 通訊工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 在傳統的正交分頻多工(OFDM)系統線性波束形成(beamforming)偵測中，遇到複雜通道或是不好的環境時，很容易達到其工作的極限。
為了提升偵測方式的效能，本篇論文提出的方法為，將模糊類神經網路(FNN)非線性偵測方式應用於OFDM系統調適性波束形成偵測器上。
而模擬結果顯示出，比起傳統的線性波束形成器偵測方式，模糊類神經網路能在位元錯誤率(BER)部分表現更為優異。
| zh_TW |
| dc.description.abstract | In conventional orthogonal frequency division multiplexing (OFDM) systems linear beamforming detection, the encounter complex or a bad channel environment, it is easy to reach the limits of their work.
In order to enhance the performance of detection methods, this paper proposed method, the fuzzy neural network (FNN) non-linear detection methods used in OFDM system, adaptive beamforming on the sensor.
The simulation results show, compared to conventional linear beamformer detection methods, fuzzy neural network in bit error rate (BER) part was even better.
| en_US |
| DC.subject | 波束成形器 | zh_TW |
| DC.subject | 類神經網路 | zh_TW |
| DC.subject | beamforming | en_US |
| DC.subject | fuzzy nerual network | en_US |
| DC.title | 模糊類神經網路應用於調適性多天線偵測器正交分頻多工系統 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Adaptive Multi-antenna Detections for an OFDM System Using Fuzzy Neural Networks | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |