From Bidirectional Associative Memory to a noise-tolerant, robust Protein Processor Associative Memory

Qadir, Omer; Liu, Jerry; Tempesti, Gianluca; Timmis, Jon; Tyrrell, Andy M.

doi:10.1016/j.artint.2010.10.008

Cited by 10 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A complete description of the biological inspiration, learning mechanism, connection topology, and conflict resolution strategy for the (previous) version of the PPAM may be found in Qadir et al (2011). A brief introduction is presented here.…”

Section: Principle Of Protein Processingmentioning

confidence: 99%

See 1 more Smart Citation

Hardware architecture for a bidirectional hetero-associative Protein Processing Associative Memory

Qadir

Liu

Timmis

et al. 2011

2011 IEEE Congress of Evolutionary Computation (CEC)

Self Cite

View full text Add to dashboard Cite

This paper details an extension to an architecture for robust bidirectional hetero-associative recall. Our proposed Protein Processor Associative Memory (PPAM) is fundamentally different from the traditional processing methods which use arithmetic operations and consequently Arithmetic and Logic Units (ALUs). In this paper, we improve on our initial work addressing concerns surrounding hardware implementation. We present the improved computational architecture, coupled with a corresponding hardware architecture for implementation. Results of applying the hardware implementation on a small dataset are included, along with reports from synthesis tools about hardware utilisation.

show abstract

Section: Principle Of Protein Processingmentioning

confidence: 99%

“…Furthermore, it guarantees perfect recall of all training pairs if it is possible to store them as stable states in the correlation matrix. Qadir et al (2011) compares the Protein Processor Associative Memory with the original BAM and PRLAB.…”

Section: Introductionmentioning

confidence: 99%

Hardware architecture for a bidirectional hetero-associative Protein Processing Associative Memory

Qadir

Liu

Timmis

et al. 2011

2011 IEEE Congress of Evolutionary Computation (CEC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Arya et al [15] recognized human faces using Parallel Associative Memory. Qadir et al [16] [17] constructed and evaluated the performance of associative memories when they are used as a controller of a robot where sensory inputs contain errors. Wen et al [18] established memristive neural network based on the knowledge of memristor and recurrent neural network and applied for adaptive lag synchronization.…”

Section: Introductionmentioning

confidence: 99%

Restricted Boltzmann machine associative memory

Nagatani

Hagiwara

2014

2014 International Joint Conference on Neural Networks (IJCNN)

View full text Add to dashboard Cite

Restricted Boltzmann machine associative memory (RBMAM) is proposed in this paper. RBMAM memorizes patterns using contrastive divergence learning procedure. It recalls by calculating the reconstruction of pattern using conditional probability. In order to examine the performance of the proposed RBMAM, extensive computer simulations have been carried out. As the result, it has shown that the performance of RBMAM is overwhelming compared with the conventional neural network associative memories. For example as for storage capacity, RBMAM can store about from 2N hidden to 4N hideen patterns, where N hidden denotes the number of neurons in the hidden layer. Similarly we have obtained superior performance of RBMAM in respect of noise tolerance and pattern complement.

show abstract

“…28 In this work we report a new model system activated by enzymes as signals and accomplishing associative memory. It is important to emphasize that associative memory 29 is a concept that has been studied for a long time 30 and in diverse fields, 31 but at the same time it has been a subject of active recent research [32][33][34][35] driven by conceptual interest and also by the promise of adding adaptive capabilities to information processing systems. However, despite active research into the area, very few biomolecular systems based on proteins 36,37 or DNA [38][39][40] mimicking associative memory in vitro have been realized.…”

mentioning

confidence: 99%