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Currently, the leading paradigm in attractor neural networks memory models is the Hopfield model [14] with possible variations, including activation functions, neural firing, density of the neural connections, and the memory loading paradigms [15] [22].
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When "memory models" are based on future times, current estimates are auto-correlated with future states.
cJVM's architecture, its unique object model, thread, and memory models, were described by Y. Aridor et al. (1999, in "International Conference on Parallel Processing, September 21 24) and at http://www.haifa.il.ibm.com/projects/systech/cjvm.html.html
These matrix memory models are content-addressable and fault-tolerant, and are well known to share with humans the ability of generalization and universalization [ 14].
The delayed model (or memory model) is quite interesting from the mathematical point of view.
The shared memory model is based on a Parallel RAM (PRAM) [10].
The memory model is defined in terms of thread-local Instruction Reordering axioms and Store Atomicity, which describes inter-thread communication via memory.
Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network.
We conclude that context-sensitive associative memory model is a promising alternative in the development of accuracy diagnostic tools.
The ANN memory model was used to store the load patterns and their related optimal schedules.
Hence, the theoretical concepts described against social capital and memory model are transformed into agents' behavior and integrated in the overall model.
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