Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning
Quantum-inspired computing is an emerging research area, which has significantly improved the capabilities of conventional algorithms. In general, quantum-inspired hopfield associative memory (QHAM) has demonstrated quantum information processing in neural structures. This has resulted in an exponen...
Main Authors: | Masuyama, Naoki, Loo, Chu Kiong, Seera, Manjeevan, Kubota, Naoyuki |
---|---|
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2018
|
Subjects: |
Similar Items
-
Personality affected robotic emotional model with associative memory for human-robot interaction
by: Masuyama, Naoki, et al.
Published: (2018) -
Meta-cognitive Recurrent Recursive Kernel OS-ELM for concept drift handling
by: Liu, Zongying, et al.
Published: (2019) -
Semi-supervised topo-Bayesian ARTMAP for noisy data
by: Nooralishahi, Parham, et al.
Published: (2018) -
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
by: Masuyama, Naoki, et al.
Published: (2019) -
An iterative incremental learning algorithm for complex-valued hopfield associative memory
by: Masuyama, N., et al.
Published: (2016)