Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Journal of Data Acquisition & Processing》 2001-01
Add to Favorite Get Latest Update

Data Compression by Improved Exponential Bidirectional Associative Memory Model

Liu Zheng Zhang Benzhu Chen Songcan College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics Nanjing 210016,P.R.China  
Improved exponential bidirectional associative memory model(IeBAM), which was developed from eBAM by adding an intraconnection to the exponents, is a neural network with higher storage capacity and correcting error capability than eBAM. Using IeBAM′s high capacity and correcting error capability and the ordered histogram technique, a data compression algorithm with better efficiency is achieved, and then a new data compression algorithm to existing data compression method is supplied. Finally, simulational results of computer verify that the effect of data compression with IeBAM is much better than that with eBAM.
【Fund】: 教育部青年骨干教师基金资助项目
【CateGory Index】: TN919.8
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved