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Information storage capacity of incompletely connected associative memories

Holger Bosch, Franz J. Kurfess
1998 Neural Networks  
In this paper, the memory capacity of incompletely connected associative memories is investigated. First, the capacity is derived for memories with fixed parameters.  ...  The maximum capacity grows with increasing connectivity of the memory and requires sparse input and output patterns.  ...  Storage capacity of the associative memory The capacity of an associative memory is defined as the ratio of the information stored in the memory and its total size: C ¼ I ZMN The size is given by the connectivity  ... 
doi:10.1016/s0893-6080(98)00035-5 pmid:12662789 fatcat:ttwn2utjgran5mpedoeldvkeka

TOLERANCE OF A BINARY ASSOCIATIVE MEMORY TOWARDS STUCK-AT-FAULTS [chapter]

U. Rueckert, H. Surmann
1991 Artificial Neural Networks  
The associative memory linder consideration is based on distributed storage of Information and is of the type analyzed by Palm (1980).  ...  The focus of the paper is on the effect of stuck-at-faults concerning the connection weights of an associative memory.  ...  The model under consideration is an associative memory based on distributed storage of information which will be described in the following section.  ... 
doi:10.1016/b978-0-444-89178-5.50050-6 fatcat:xbnkoc7w5ffzjp3niby4jxhutq

A model for structural plasticity in neocortical associative networks trained by the hippocampus

Andreas Knoblauch, Friedrich T Sommer, Marc-Oliver Gewaltig, Rüdiger Kupper, Ursula Körner, Edgar Körner
2007 BMC Neuroscience  
Associative networks such as the Hopfield or Willshaw model are at the heart of many cortex theories and have been analyzed for a long time with respect to information storage capacity and plausible retrieval  ...  However, for incompletely connected networks the capacity per synapse can be massively reduced or even vanish, depending on the retrieval algorithm [4] .  ...  Associative networks such as the Hopfield or Willshaw model are at the heart of many cortex theories and have been analyzed for a long time with respect to information storage capacity and plausible retrieval  ... 
doi:10.1186/1471-2202-8-s2-s14 fatcat:757yzqlq3fa2nowbcibubhb5kq

The Associative Recall of Spatial Correlated Patterns [chapter]

Jana Štanclová
2006 Lecture Notes in Computer Science  
The HAM2-model uses the information recalled by the "previous-layer" to find an appropriate subset of "next-level" associative memories.  ...  However, the performance of standard associative memories is very sensitive to the number of stored patterns and their mutual correlations.  ...  This work was partially supported by the Ministry of Education of the Czech Republic (grant MSM0021620838).  ... 
doi:10.1007/11892755_56 fatcat:kquartswn5ebvice4336nhkz5e

Pattern Completion and Pattern Separation Mechanisms in the Hippocampus [chapter]

Edmund T. Rolls
2015 The Neurobiological Basis of Memory  
Acknowledgments Different parts of the research described here were supported by Program  ...  The Dilution of the CA3 Recurrent Collateral Connectivity Enhances Memory Storage Capacity and Pattern Completion Figure 4.2 shows that in the rat, there are approximately 300,000 CA3 neurons, but only  ...  In humans, with effectively two separate CA3 networks, one on each side of the brain, the memory storage capacity may be doubled, as the capacity is set by the number of recurrent collaterals per neuron  ... 
doi:10.1007/978-3-319-15759-7_4 fatcat:77nugpooh5bp3bxcd22bf3dgdy

A modular attractor associative memory with patchy connectivity and weight pruning

Cristina Meli, Anders Lansner
2013 Network  
We show that the storage capacity of the modular network is comparable with the theoretical values estimated for simple associative memories and furthermore we introduce a new technique to reduce the connectivity  ...  We show that the storage capacity of the modular network is comparable with the theoretical values estimated for simple associative memories and furthermore we introduce a new technique to reduce the connectivity  ...  In fact, in the context of a binary associative memory, which has maximum information capacity when the connection matrix is filled to 50%, if we can avoid storing non-used connections we would about double  ... 
doi:10.3109/0954898x.2013.859323 pmid:24251411 fatcat:rbqhdakw3nccpdoaokizmvv5wu

The mechanisms for pattern completion and pattern separation in the hippocampus

Edmund T. Rolls
2013 Frontiers in Systems Neuroscience  
Recall of information from CA3 is implemented by the entorhinal cortex perforant path synapses to CA3 cells, which in acting as a pattern associator allow some pattern generalization.  ...  network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory  ...  Memory Storage Capacity and Pattern Completion.  ... 
doi:10.3389/fnsys.2013.00074 pmid:24198767 pmcid:PMC3812781 fatcat:x3h755woy5chpo7dk2mqzga3ca

Distance-Based Sparse Associative Memory Neural Network Algorithm for Pattern Recognition

Lei Chen, Songcan Chen
2006 Neural Processing Letters  
Such a new configuration can reduce the connection complexity of conventional fully connected associative memories so that makes AM' VLSI implementation easier.  ...  A sparse two-Dimension distance weighted approach for improving the performance of exponential correlation associative memory (ECAM) and modified exponential correlation associative memory (MECAM) is presented  ...  NJUPT "QingLan" Project Foundation and the Returnee's Foundation of China Scholarship Council for partial supports, respectively.  ... 
doi:10.1007/s11063-006-9012-y fatcat:ttp2yupd6jcp3oj4l5z3bzcq7y

Tree-like hierarchical associative memory structures

João Sacramento, Andreas Wichert
2011 Neural Networks  
These networks offer very generous storage capacities (both asymptotic and finite) at the expense of sparse coding.  ...  Instead of modelling the network as a single layer of neurons we suggest a hierarchical organization where the information content of each memory is a successive approximation of one another.  ...  Acknowledgements The authors wish to express their gratitude towards Jan Cederquist and the anonymous reviewers for their helpful and incisive comments on early versions of this manuscript.  ... 
doi:10.1016/j.neunet.2010.09.012 pmid:20970304 fatcat:qtuqo5bcc5d4hjs72ycr7mhrsq

Hybrid Network Learning

Gnanambigai Dinadayalan, P. Dinadayalan, K. Balamurugan
2011 International Journal of Computer Applications  
This paper proposes Neural Network architecture for implementing associative memory. A new model has been developed that has good learning structure and high storage capacity.  ...  The associative memory is applied for pattern association. Associative memory is content-addressable structure that maps a set of input patterns to a set of output patterns.  ...  Associative memory stands as the most likely model for cognitive memories, as well. Humans retrieve information best when it can be linked to other related information.  ... 
doi:10.5120/2616-3347 fatcat:wo2fjxnyzzekvkwgtieqx5xxwm

Memory retrieval time and memory capacity of the CA3 network: Role of gamma frequency oscillations

L. de Almeida, M. Idiart, J. E. Lisman
2007 Learning & memory (Cold Spring Harbor, N.Y.)  
The nature of the information that is associated in CA3a is discussed.  ...  A second goal of our work was to evaluate previous methods for estimating the memory capacity (P) of CA3.  ...  Estimating the memory capacity of CA3 The calculation of memory capacity of a network requires an analytical framework. Several such frameworks for the study of associative memory have been proposed.  ... 
doi:10.1101/lm.730207 pmid:18007022 pmcid:PMC2080581 fatcat:houxgkufwzdkbfbsss4dxobg3e

Implementation of Hopfield Neural Network for its Capacity with Finger Print Images

Ramesh Chandra, Somesh Kumar, Puneet Goswami
2016 International Journal of Computer Applications  
Performance is measured with respect to storage capacity; recall of distorted or noisy patterns. Here we test the accretive behavior of the Hopfield neural network.  ...  This paper analyzes the Hopfield neural network for storage and recall of fingerprint images.  ...  Correspondingly, associative memory is the function where the brain is able to store and recall information, given partial knowledge of the information content [1] .  ... 
doi:10.5120/ijca2016909625 fatcat:bw52jgwjx5cfvpfwmajswsfsly

Hebbian learning and temporary storage in the convergence-zone model of episodic memory

Michael Howe, Risto Miikkulainen
2000 Neurocomputing  
The Convergence-Zone model shows how sparse, random memory patterns can lead to one-shot storage and high capacity in the hippocampal component of the episodic memory system.  ...  This paper presents a biologically more realistic version of the model, with continuously-weighted connections and storage through Hebbian learning and normalization.  ...  The connections between the feature map and the binding layer of the convergence zone memory are represented as binary values, and learning occurs by switching a given set of connections from inactive  ... 
doi:10.1016/s0925-2312(00)00248-4 fatcat:vdxfeccewvcdjbpcukaob7p22a

Quantum Associative Memory in HEP Track Pattern Recognition [article]

Illya Shapoval, Paolo Calafiura
2019 arXiv   pre-print
In this work we discuss the potential of Quantum Associative Memory (QuAM) in the context of LHC data triggering.  ...  We examine the practical limits of storage capacity, as well as store and recall errorless efficiency, from the viewpoints of the state-of-the-art IBM quantum processors and LHC real-time charged track  ...  In this paper, we consider Quantum Associative Memory (QuAM) [4] [5] [6] [7] [8] -a quantum variant of AM based on quantum storage medium and two quantum algorithms for information storage and recall  ... 
arXiv:1902.00498v2 fatcat:4wqpdqna35d7hkw2qxng2qeeli

Cognitive approaches to the development of short-term memory

Susan E. Gathercole
1999 Trends in Cognitive Sciences  
The capacity to retain information for brief periods of time increases dramatically during the childhood years.  ...  , including perceptual analysis, construction and maintenance of a memory trace, retention of order information, rehearsal, retrieval and redintegration.  ...  Acknowledgements The preparation of this work was supported by the Medical Research Council of Great Britain.  ... 
doi:10.1016/s1364-6613(99)01388-1 pmid:10529796 fatcat:kkaz6mbrpjf55ewxydbt2fep3a
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