Multidirectional associative memory with self-connections
نویسندگان
چکیده
منابع مشابه
Multistability in a Multidirectional Associative Memory Neural Network with Delays
This paper focuses on the multidirectional associative memory (MAM) neural networks with m fields which is more advanced to realize associative memory. Based on the Brouwer fixed point theorem and Dini upper right derivative, it is confirmed that the multidirectional associativememory neural network can have 3 equilibria and 2 equilibria of them are stable, where l is a parameter associated wit...
متن کاملAssociative memory model with long-tail-distributed Hebbian synaptic connections
The postsynaptic potentials of pyramidal neurons have a non-Gaussian amplitude distribution with a heavy tail in both hippocampus and neocortex. Such distributions of synaptic weights were recently shown to generate spontaneous internal noise optimal for spike propagation in recurrent cortical circuits. However, whether this internal noise generation by heavy-tailed weight distributions is poss...
متن کاملHigh Performance Associative Memory Models and Symmetric Connections
Two existing high capacity training rules for the standard Hopfield architecture associative memory are examined. Both rules, based on the perceptron learning rule produce asymmetric weight matrices, for which the simple dynamics (only point attractors) of a symmetric network can no longer be guaranteed. This paper examines the consequences of imposing a symmetry constraint in learning. The mea...
متن کاملAssociative Memory with Dynamic Synapses
We have examined a role of dynamic synapses in the stochastic Hopfield-like network behavior. Our results demonstrate an appearance of a novel phase characterized by quick transitions from one memory state to another. The network is able to retrieve memorized patterns corresponding to classical ferromagnetic states but switches between memorized patterns with an intermittent type of behavior. T...
متن کاملSymbolic Memory of Motion Patterns by an Associative Memory Dynamics with Self-organizing Nonmonotonicity
We previously proposed a memory system of motion patterns[4] using an assotiative memory model. It forms symbolic representations of motion patterns based on correlations by utilizing bifurcations of attractors depending on the parameter of activation nonmonotonicity. But the parameter had to be chosen appropreately to some degree by manual. We propose here a way to provide the paremeter with s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nonlinear Theory and Its Applications, IEICE
سال: 2014
ISSN: 2185-4106
DOI: 10.1587/nolta.5.222