Properties of bidirectional associative memory and capacity considerations (Record no. 95205)

MARC details
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005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260818174918.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170699s1995 th uzm rtt 00| a1eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b11531423
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Diss. no. CS-95-1
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Haryono
245 10 - TITLE STATEMENT
Title Properties of bidirectional associative memory and capacity considerations
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Bangkok :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 1995
300 ## - PHYSICAL DESCRIPTION
Extent 129 leaves
490 1# - SERIES STATEMENT
Series statement Dissertation ;
Volume/sequential designation no. CS-95-1
500 ## - GENERAL NOTE
General note A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Technical Science.
520 ## - SUMMARY, ETC.
Summary, etc. Capacity is an important factor in the concept of memory. Bidirectional Associative Memory (BAM), one model of associative memory which also belongs to a class of neural networks, has aroused much interest because of its potential benefits. A promising model, its information processing mechanism needs investigations. It is desirable that BAM should have as large a capacity as possible, i.e., the ability to store and recall properly a large number of pattern pairs. It storage capacity has been estimated at C< min (n,p). where n and p are the dimensions of pattern pairs A and B respectively. The capacity is somewhat peculiar in that the network can recover only C memories out of the total 2n and 2p states available in the network as cube corners of n- and p- dimensional hypercubes for patterns A and B respectively. Such a capacity can be considered very low. Two issues are addressed in this study. Firstly, it investigates some important properties of BAM and proposes an improved capacity estimate. Those properties are the encoding form of the input pattern pairs as well as their decoding, the orthogonality of the pattern pairs, the similarity of associated patterns, and the density of the pattern pairs. Secondly, it proposes an implementation approach to improve the storage capacity. The approach embraces three proposed methods, i.e. the Bipolar-orthogonal Augmentation, the Set Partition, and the combined method. Along with those proposed methods is the construction of the set of bipolar orthogonal patterns. Four important properties of BAM have been investigated and analyzed. First, bipolar encoding-decoding gives the best performance over the other possible encoding-decoding forms. Second, for a trivial case is that BAM's capacity will be bounded at C= min (n,p) when all the pattern pairs are orthogonal. When they are non-orthogonal, the capacity decreases. Third, for another trivial case where the key pattern is similar to the associated pattern, i.e. A=B and thus n=p shows that BAM can store and properly recall all 2n available states of the pattern pairs if it is encoded in bipolar form. Fourth, patterns encoded in a balanced density give better recall operation than the other encoding. The implementation approach consists of modification of BAM's original architecture, and handing of input pattern pairs. The modification of BAM's original architecture includes modification of related BAM algorithms. Two methods, Set Partition and Bipolar-orthogonal Augmentation are proposed where each of them guarantees the recall of all pattern pairs. Both methods can be combined to produce optimum performance. For the purpose of the approach, an algorithm to construct a set of bipolar-orthogonal partners has been developed. Sufficient conditions for the length of augmentation for which all of the patten pairs can be stored and properly recalled in BAM have been derived. The trade-offs between the improvement of the capacity and the memory complexity are also discussed.
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Asian Institute of Technology, 1995
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Neural networks (Computer science)
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name H.N. Phien,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name R. Sadananda,
Relator term Examination comittee
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Kaew Nualchawee,
Relator term Examination comittee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Government of Indonesia,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Dissertation ;
Volume/sequential designation no. CS-95-1
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B00303">http://203.159.5.9/ait-thesis/detail.php?q=B00303</a>
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Cataloger's initials, CIN (RLIN) 960910
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945 ## - LOCAL PROCESSING INFORMATION (OCLC)
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l mnarc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 20-AIT Publication
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 40-Archives
909 ## - LOCAL ITEMS USED
Barcode Barcode : 30050004008479
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      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026   AIT Diss. no. CS-95-1 30050004008479 18/08/2026 1 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026   AIT Diss. no. CS-95-1 30050004008503 18/08/2026 2 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 18/08/2026   AIT Diss. no. CS-95-1 30050160037601 18/08/2026   18/08/2026 40-Archives
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