查詢結果分析
相關文獻
- Neural-net Decoders for Linear Block Codes
- Design of Probabilistic Neural Networks for Discrete Variables
- 兩種晶圓缺陷辨識技術之比較
- Quantitative Comparison between Artificial Neural Networks and Bilinear Interpolation to Predict a Real Robot's Sonar Sensor Readings
- An Implementation of Distributed Framework of Artificial Neural Network for Big Data Analysis
- 深度學習在Smart Beta交易策略之應用
- 運用人工智慧發掘具訴訟風險專利
- Neural Network Procedures for Taguchi's Dynamic Problems
- A Fast and Efficient Competitive Learning Design Algorithm Based on Weight Vector Training in Transform Domain
- 專家系統振動訊號圖型判別之研究
頁籤選單縮合
題 名 | Neural-net Decoders for Linear Block Codes=線性區塊碼於類神經解碼器之應用 |
---|---|
作 者 | 張順雄; 盧守義; | 書刊名 | Journal of the Chinese Institute of Electrical Engineering |
卷 期 | 5:4 1998.11[民87.11] |
頁 次 | 頁333-343 |
分類號 | 312.2 |
關鍵詞 | 類神經網路; 漢明網路; 線性區塊碼; 錯誤更正碼; 感知器; Neural network; Hamming network; Linear block codes; Error correcting codes; Perceptron; |
語 文 | 英文(English) |
中文摘要 | 本論文提出以類神經網路應用於數位通訊系統中錯誤更正解碼器之新方法。論文 中亦提出一種具有較少權重連接數目及較快收斂速度之修正型漢明網路,其在全部類神經解 碼器之應用上並有相當的改良。為了降低解碼時間,因此,首度將感知器應用於部分類神經 解碼器上。由於本論文所應用之類神經解碼器具有整數權重的特性,故其適用於 VLSI 的硬 體實現。 經由電腦模擬結果顯示,如果傳輸過程中,僅有 t 個錯誤位元以發生錯誤,則必 能達到 100 %的錯誤更正率。因此,證實類神經解碼器可應用於傳統解碼器上。 |
英文摘要 | In this paper, we present new methods to apply neural networks on the error correcting decoder of a digital communication system. A modified Hamming network which contains less connection numbers and faster convergences speed is proposed as an improvement for a total neural-net decoder. In order to decrease decoding time, a new attempt is made with the application of Perceptrons on the partial neural-net decoder. Since the integral weight feature of the neural-net decoder, it is convenient for VLSI implementation. The results of computer simulation show that it is able to achieve a 100% error correcting rate if there are only limited t error bits in the transmission. So neural-net decoders can be applied on traditional decoders indeed. |
本系統中英文摘要資訊取自各篇刊載內容。