Adaptive Resonance Theory

By T. Tanaka, A. Weitzenfeld. 2002

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Citations in the corpus

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect (2014, background): “Such approaches include ART-type architectures [90], emergent category-specific modularity [93], hard-wired modularity [94], and also ideas involving grandmother cells [95] or, in technical terms, look-up-tables [16].”
A revised model of short-term memory and long-term learning of verbal sequences (2006, methodology): “This matching process enables the model to detect whether a sequence is familiar or not, in a manner reminiscent of Adaptive Resonance Theory (Grossberg, 1976, see also Carpenter & Grossberg, 2003).”
Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors (2012, background): “Conceptually the notion of a global attractor model of the brain network is not new (Grossberg, 1980; Hopfield, 1984; Carpenter and Grossberg, 2003; Haken, 2004).”
The use of acoustic indices to determine avian species richness in audio-recordings of the environment (2014, unknown): “We implement a modified version of the ART1 unsupervised iterative learning algorithm designed to cluster binary input vectors (Grossberg and Carpenter, 2002).”
Network Anomaly Detection: Methods, Systems and Tools (2014, methodology): “NSOM (Network Self-Organizing Maps) [139] is a network IDS developed using Self-Organizing Maps (SOM).”
How Do Expectations Shape Perception? (2018, background): “At the same time, there are several other computational theories of perceptual inference that share the computational goal of optimal inference under uncertainty, such as pattern theory [119], adaptive resonance theory [106], particle filtering [79], free energy and active inference [120], and sampl”
Survey of clustering algorithms (2005, background): “Two variants of kernel--means were introduced in [66], motivated by SOFM and ART networks.”
Histology image analysis for carcinoma detection and grading (2012, methodology): “Without a set of labeled samples, unsupervised techniques, such as K-means, fuzzy c-means, ISODATA clustering, Meanshift [40], self-organizing map [63], and adaptive resonance theory [23], can be applied to group image points to different objects.”
Controlling Recurrent Neural Networks by Conceptors (2014, methodology): “In adaptive resonance theory [43], the role of a trust measure is filled by the ratio between the norm of a top-down pattern interpretation over the norm of an input pattern; the functional effects of this ratio for further processing depends on whether that ratio is less or greater than a certain “”
40 years of cognitive architectures: core cognitive abilities and practical applications (2018, background): “Conclusion Overall, visual attention is largely overlooked in cognitive architectures research with the exception of the biologically plausible visual models (e.g. ART) and the architectures that specifically focus on vision research (ARCADIA, STAR).14 This is surprising because strong theoretical a”
2007 Special Issue: Consciousness CLEARS the mind (2007, unknown): “…of the visual system, and it has been proposed how these mechanisms are realized by laminar circuits of visual cortex as they interact with specific and nonspecific thalamic nuclei (Grossberg, 2003b; Grossberg and Versace, 2007; Raizada and Grossberg, 2003; Versace and Grossberg, 2005, 2006).”
Event perception: a mind-brain perspective. (2007, methodology): “More formal modeling, particularly aimed at exploring the relationship between the reset mechanism proposed here and that used in ART models (Carpenter & Grossberg, 2003; Grossberg, 1999), would be very productive.”