Self-organization and associative memory

by Teuvo Kohonen

Publisher: Springer-Verlag in Berlin, New York

Written in English
Cover of: Self-organization and associative memory | Teuvo Kohonen
Published: Pages: 255 Downloads: 325
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Subjects:

  • Self-organizing systems.,
  • Memory.,
  • Associative storage.

Edition Notes

StatementTeuvo Kohonen.
SeriesSpringer series in information sciences ;, 8
Classifications
LC ClassificationsQ325 .K64 1984
The Physical Object
Paginationxii, 255 p. :
Number of Pages255
ID Numbers
Open LibraryOL3174560M
ISBN 10038712165X
LC Control Number83016919

Associative memory is a system that associates two patterns (X, Y) such that when one is encountered, the other can be recalled. The associative memory are of two types: auto-associative memory and hetero-associative memory. Auto-associative memory Consider, y[1], y[2], y[3], y[M], be the number of storedFile Size: KB. Fuzzy Associative memory, and, of course, the Feedforward Backpropagation network (aka Multilayer Perceptron). You should get a fairly broad picture of neural networks and fuzzy logic with this Size: 1MB. In psychology, associative memory is defined as the ability to learn and remember the relationship between unrelated items. This would include, for example, remembering the name of someone or the aroma of a particular perfume. This type of memory deals specifically with the relationship between these different objects or concepts. Structure of a Computer System Brief history of computers, Von Neumann architecture, Functional units, Bus structures and Interconnection networks, Types and Computer Arithmetic Scalar data types, Fixed and floating point numbers, Signed numbers, Integer arithmetic, 2 s Complement multiplication, Booths algorithm, Hardware 3/5(3).

Hetero Associative memory. Similar to Auto Associative Memory network, this is also a single layer neural network. However, in this network the input training vector and the output target vectors are not the same. The weights are determined so that the network stores a set of patterns. Many memory techniques involve creating unforgettable imagery, in your mind’s eye. That’s an act of imagination. Creating really weird imagery really quickly was the most fun part of my training to compete in the US Memory Competition. Yates writes that the earliest known book with memory tips dates to 90BC.   Associative memory 1. Associative Memory Computation Ameer Mehmood Adeel Ahmad 2. Introduction To search particular data in memory, data is read from certain address and compared if the match is not found content of the next address is accessed and compared. This goes on until required data is found. The number of access . cache to be composed of associative memory holding both the memory address and the data for each cached line. The incoming memory address is simultaneously compared with all stored addresses using the internal logic of the associative memory, as shown in Fig If a match is fund, the corresponding data is read out. Single words formFile Size: KB.

Associative memory: A type of computer memory from which items may be retrieved by matching some part of their content, rather than by specifying their address (hence also called associative storage or Content-addressable memory (CAM).) Associative memory is much slower than RAM, and is rarely encountered in mainstream computer example, . Autoassociative memory. Autoassociative memories are capable of retrieving a piece of data upon presentation of only partial information [clarification needed] from that piece of data. Hopfield networks have been shown to act as autoassociative memory since they are capable of remembering data by observing a portion of that data.. Examples. For example, the sentence . Most associative memory implementations are realized as connectionist networks. Hopfield's collective computation network [1] serves as an excellent example of an autoassociative memory, whereas Rosenblatt's perceptron [3] is often utilized as a heteroassociator. The authors study a modified Hopfield model of associative memory with a learning rule proposed by Personnaz et al () for the special case of ultrametrically correlated patterns. The formula for the synaptic strength tells the 'teacher' how much stress to put on details compared to averages at each by:

Self-organization and associative memory by Teuvo Kohonen Download PDF EPUB FB2

While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Self-organization and associative memory book (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in Cited by: Buy Self-Organization and Associative Memory (Springer Series in Information Sciences) on FREE SHIPPING on qualified orders Self-Organization and Associative Memory (Springer Series in Information Sciences): Kohonen, Teuvo: : BooksFormat: Paperback.

While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A Brand: Springer-Verlag Berlin Heidelberg.

Self-Organization and Associative Memory Professor Teuvo Kohonen (auth.) While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol.

17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in Several working associative memory archi­ tectures, based solely on optical technologies, have been constructed in recent years.

For this reason it was felt necessary to include a separate chapter (Chap. 10) which deals with the optical associative : Springer-Verlag Berlin Heidelberg.

Self-Organization and Associative Memory by Teuvo Kohonen,available at Book Depository with free delivery worldwide/5(3). Verified book recommendations from people we look up to. This website is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and.

About this book Introduction While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Self-organization and associative memory book (IS 8), the book actually stems from Vol.

17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in The chapter concludes with a brief discussion of correlation matrix memory.

Chapter 7, “Pattern Recognition” (25 pages), presents only those aspects of pattern recognition that the author believes to be relevant to self-organization and associative memory. Self-Organization and Associative Memory 作者: Teuvo Kohonen 出版社: Springer-Verlag Berlin and Heidelberg GmbH & Co.

K 出版年: 页数: 定价: USD 装帧: Paperback ISBN: Author: Teuvo Kohonen. Several working associative memory archi­ tectures, based solely on optical technologies, have been constructed in recent years. For this reason it was felt necessary to include a separate chapter (Chap. 10) which deals with the optical associative memories.

Part of its con­ tents is taken over from the first edition. Self Organization And Associative Memory. While the present edition is bibliographically the third one of Vol.

8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in /5(3).

Self-organization and associative memory (Springer series in information sciences) by Kohonen, Teuvo and a great selection of related books, art. The book presents new formalisms of pattern processing: orthogonal projectors, optimal associative mappings, novelty filters, subspace methods, feature-sensitive units, and self-organization of topological maps, with all their computable by:   Self-organization and associative memory by Teuvo Kohonen Published by Springer-Verlag in Berlin, New :   While the present edition is bibliographically the third one of Vol.

8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in Author: Teuvo Kohonen. A Self-organizing Associative Memory System for Control Applications best aatching cell the template vector 10 of the accessed association cell is compared to the stiaulus and a differ­ ence vector is calculated.

= t. - L." v i = O, •••,n s n number of searching steps s (1). Self-organization and associative memory. Berlin ; New York: Springer-Verlag, © (OCoLC) Online version: Kohonen, Teuvo. Self-organization and associative memory. Berlin ; New York: Springer-Verlag, © (OCoLC) Material Type: Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Teuvo.

Addeddate Identifier SelfOrganizationAndAssociativeMemory Identifier-ark ark://t53f9w38z Ocr ABBYY FineReader Ppi Scanner. Self-organization and Associative Memory: 3rd Edition () by T Kohonen Add To MetaCart. Tools. Sorted by: Results 1 - 10 of Next 10 → Discriminant Analysis by. Self-organization and associative memory.

Berlin ; New York: Springer-Verlag, (OCoLC) Material Type: Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Teuvo Kohonen. SIAM Review. Article Tools. Add to my favoritesCited by: 1.

While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol.

17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in That book was the first monograph on distributed associative memories. Bidirectional Associative Memories (BAM) are systems that allow to associate pairs of patterns.

Once a memory has learned, patterns can be recalled in two directions. BAMs have many applications in pattern recognition and image : Acevedo-MosquedaMaria Elena, Yáñez-MárquezCornelio, Acevedo-MosquedaMarco Antonio. The nature of associative memory Neural networks and associative memory A physical analogy with memory The Hopfield net Finding the weights Storage capacity The analogue Hopfield model Combinatorial optimization Feedforward and recurrent associative nets Summary Notes 8 Self-organization 6File Size: 4MB.

"Self-Organization and Associative Memory Ammareal» Visit my store Description Titlee: Self-Organization and Associative Memory Author(s): Teuvo Kohonen Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Publishing year: Sate: Second Hand – Good isbn: Comment: Former library book.

Edition SoilingBook Edition: 2nd Edition. The book presents new formalisms of pattern processing: orthogonal projectors, optimal associative mappings, novelty filters, subspace methods, feature-sensitive units, and self-organization of Author: Andreas Wichert.

A model of the hippocampus combining self-organization and associative memory function. Title: Self-organization and associative memory: Authors: Kohonen, Teuvo: Publication: Applied Optics, Vol Issue 2, Janupp A model of the hippocampus combining self­ organization and associative memory function.

Michael E. Hasselmo, Eric Schnell Joshua Berke and Edi Barkai Dept. of Psychology, Harvard University 33 Kirkland St., Cambridge, MA [email protected] Abstract A model of the hippocampus is presented which forms rapid self -orga­.

CONCLUSIONS Associative memory-type networks offer the advantage of fast learning, while maintaining the degree of generalization often sufficient for a broad class of manufacturing applications. Some examples of the use of such networks in machine vision, robotics, and measurement systems were given in this : M.B.

Zaremba.A. Funke and Ch. Pintaske, Acceleratorboard for neural associative memories, Neurocomput- ing 5 () A parallel and scalable architecture for rapid prototyping as well as for fast emulation of neural associative memories is described.

The implementation is based on custom available components: RAMs and Field Programmable Gate Arrays Cited by: Kohonen T., Self-Organisation and Associative Memory ( Springer-Verlag) Christopher Langton (ed.), Artificial Life - Proceedings of the first ALife conference at Santa Fe ( Addison Wesley).

Technical (several later volumes are available but this is the best introduction).