In this research paper, a novel Convolutional Associative Memory is proposed. In the proposed model, Synapse of each neuron is modeled as a Linear FIR filter. The dynamics of Convolutional Associative Memory is discussed. A new method called SubSampling is given. Proof of convergence theorem is discussed. An example depicting the convergence is shown. Special cases to the proposed convolutional...

The paper concentrates on analyzing associative properties of Artificial Immune Systems, especially on immunological memory, which is a member of a class of sparse and distributed associative memories [18]. This class of memories derives its associative and robust nature by sparsely sampling the input space and distributing the data among many independent agents [16]. Immunological memory is on...

Associative recognition and recall depend on structures in the medial temporal lobes (MTLs). There is disagreement about whether associative memory is functionally heterogeneous, whether it is functionally distinct from intra-item associative memory and how the MTLs contribute to this kind of memory. Despite an increase in research on associative memory, work has lacked a theoretical framework ...

As an important artificial neural network, associative memory model can be employed to mimic human thinking and machine intelligence. In this paper, first, a multi-valued many-to-many Gaussian associative memory model (MGAM) is proposed by introducing the Gaussian unidirectional associative memory model (GUAM) and Gaussian bidirectional associative memory model (GBAM) into Hattori et al’s multi...

Although the hippocampus is implicated in both spatial navigation and associative memory, very little is known about whether individual differences in the 2 domains covary. People who prefer to navigate using a hippocampal-dependent place strategy may show better performance on associative memory tasks than those who prefer a caudate-dependent response strategy (Bohbot, Gupta, Banner, & Dahmani...