Bidirectional associative memories
@article{Kosko1988BidirectionalAM,
title={Bidirectional associative memories},
author={Bart Kosko},
journal={IEEE Trans. Syst. Man Cybern.},
year={1988},
volume={18},
pages={49-60}
}Stability and encoding properties of two-layer nonlinear feedback neural networks are examined. Bidirectionality is introduced in neural nets to produce two-way associative search for stored associations. The bidirectional associative memory (BAM) is the minimal two-layer nonlinear feedback network. The author proves that every n-by-p matrix M is a bidirectionally stable heteroassociative content-addressable memory for both binary/bipolar and continuous neurons. When the BAM neutrons are…
1,909 Citations
Adaptive bidirectional associative memories.
- Computer ScienceApplied optics
- 1987
The BAM correlation encoding scheme is extended to a general Hebbian learning law and every BAM adaptively resonates in the sense that all nodes and edges quickly equilibrate in a system energy local minimum.
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- 2006
This paper introduces a new bidirectional heteroassociative memory model that uses a simple self-convergent iterative learning rule and a new nonlinear output function that can learn online without being subject to overlearning.
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- 2000
It is shown that the Hamming attractive radius of each prototype reaches the maximum possible value and the overall network design procedure is fully scalable in the sense that any number p= or <2(min{m,n}) of bidirectional associations can be implemented.
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- 2008
A new bidirectional hetero-associative memory model for true-color patterns that uses the associative model with dynamical synapses recently introduced in Vazquez and Sossa to guarantee perfect and robust recall of the fundamental set of associations.
A Bidirectional Associative Memory Based on Optimal Linear Associative Memory
- Computer ScienceIEEE Trans. Computers
- 1996
The introduction of a nonlinear characteristic enhances considerably the ability of the BAM to suppress the noises occurring in the output pattern, and reduces largely the spurious memories, and therefore improves greatly the recall performance of theBAM.
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- Computer ScienceIEEE International Conference on Neural Networks
- 1993
The author attempts to resolve important issues on artificial neural nets, i.e., exact recall and capacity in multilayer associative memories, and completely relaxes any code-dependent conditions of the learning pairs.
Encoding Static and Temporal Patterns with a Bidirectional Heteroassociative Memory
- Computer ScienceJ. Appl. Math.
- 2011
It will be shown that the Bidirectional Associative Memory can be generalized to multiple associative memories, and that it can be used to store associations from multiple sources as well.
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- Computer ScienceApplied optics
- 1987
The bidirectional associative memory (BAM) is a powerful neural network paradigm that is well suited to optical implementation and variations on the BAM indicate some of the interesting directions this simple structure may evolve, leading in a natural progression toward the power of a model such as the Carpenter-Grossberg ART.
Learning Associative Memories by Error Backpropagation
- Computer ScienceIEEE Transactions on Neural Networks
- 2011
It is shown that the robustness in respect to acceptable noise in the input of the constructed networks is enhanced as the memory dimension increases and weakened as the number of the stored patterns grows.
A neural network based multi-associative memory model
- Computer Science1990 IJCNN International Joint Conference on Neural Networks
- 1990
An improved two-layer neural network model is presented for a multiassociative content-addressable memory that yields improved error-correction and storage capabilities and faster convergence rate, avoids the storage of complementary and false memories, and possesses analogies to biological neural networks.
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