Tech reports available: Incremental learning

[DeLiang Wang]

The following Technical Report is available via FTP/WWW:

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Incremental Learning of Complex Temporal Patterns
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DeLiang Wang and Budi Yuwono

Technical Report: OSU-CISRC-6/95-TR30
Department of Computer and Information Science, The Ohio State University

A neural model for temporal pattern generation is used and analyzed for 
training with multiple complex sequences in a sequential manner.  The 
network exhibits some degree of interference when new sequences are acquired.  
It is proven that the model is capable of incrementally learning a finite 
number of complex sequences.  The model is then evaluated with a large 
set of highly correlated sequences.  While the number of intact sequences 
increases linearly with the number of previously acquired sequences, the 
amount of retraining due to interference appears to be independent of the 
size of existing memory.  The model is extended to include a chunking 
network which detects repeated subsequences between and within sequences.  
The chunking mechanism substantially reduces the amount of retraining in 
sequential training.  Thus, the network investigated here constitutes an 
effective sequential memory.  Various aspects of such a memory are 
discussed at the end of the paper.  

(34 pages - 239 KB) 


for anonymous ftp:
       	FTP-HOST: ftp.cis.ohio-state.edu
       	FTP-filename: /pub/leon/Wang-Yuwono.tech.ps.Z

or for WWW:
	http://www.cis.ohio-state.edu/~dwang


Comments are most welcome - Please send to 
	DeLiang Wang (dwang at cis.ohio-state.edu)


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FTP instructions:

To retrieve and print the file, use the following commands:

unix> ftp ftp.cis.ohio-state.edu
Name: anonymous
Password: (your email address)
ftp> binary
ftp> cd /pub/leon
ftp> get Wang-Yuwono.tech.ps.Z
ftp> quit
unix> uncompress Wang-Yuwono.tech.ps.Z
unix> lpr Wang-Yuwono.tech.ps 
	(It may not ghostview well - missing page count with my ghostview - 
	 but it should print ok)
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