A twin-multistate quaternion Hopfield neural network (TMQHNN) is a multistate Hopfield model and can store multilevel information, such as image data. Storage capacity is an important problem of Hopfield neural networks. Jankowski et al. approximated the crosstalk terms of complex-valued Hopfield neural networks (CHNNs) by the 2-dimensional normal distributions and evaluated their storage capacities. In this work, we evaluate the storage capacities of TMQHNNs based on their idea
A model of neurons with CHN (Continuous Hysteresis Neurons) for the Hopfield neural networks is stud...
Das Hopfield Modell ist ein neuronales Netzwerk und kann als assoziativer Speicher genutzt werden. I...
A method to store each element of an integral memory set M subset of {1,2,...,K}(n) as a fixed point...
We define a Potts version of neural networks with q states. We give upper and lower bounds for the s...
We analyze the storage capacity of a variant of the Hopfield model with semantically correlated patt...
The Hopfield model is a pioneering neural network model with associative memory retrieval. The analy...
Hopfield-type, neural-network models. A mathematical framework for cornporing the two models is deve...
We analyze the storage capacity of the Hopfield model with spatially correlated patterns ¸ i (i.e....
The storage capacity of a Q-state Hopfield network is determined via finite size scaling for paralle...
The information capacity of general forms of memory is formalized. The number of bits of information...
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d...
In this thesis, the storage capacities of the Bidirectional Associative Memories (BAM) and the Hopfi...
This paper presents a further theoretical analysis on the asymptotic memory capacity of the generali...
A method to store each element of an integer-valued memory set M ⊂ {1, 2,..., K}n as a fixed point i...
WOS: A1996VL22600006This paper introduces a new family of multivalued neural networks. We have inter...
A model of neurons with CHN (Continuous Hysteresis Neurons) for the Hopfield neural networks is stud...
Das Hopfield Modell ist ein neuronales Netzwerk und kann als assoziativer Speicher genutzt werden. I...
A method to store each element of an integral memory set M subset of {1,2,...,K}(n) as a fixed point...
We define a Potts version of neural networks with q states. We give upper and lower bounds for the s...
We analyze the storage capacity of a variant of the Hopfield model with semantically correlated patt...
The Hopfield model is a pioneering neural network model with associative memory retrieval. The analy...
Hopfield-type, neural-network models. A mathematical framework for cornporing the two models is deve...
We analyze the storage capacity of the Hopfield model with spatially correlated patterns ¸ i (i.e....
The storage capacity of a Q-state Hopfield network is determined via finite size scaling for paralle...
The information capacity of general forms of memory is formalized. The number of bits of information...
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d...
In this thesis, the storage capacities of the Bidirectional Associative Memories (BAM) and the Hopfi...
This paper presents a further theoretical analysis on the asymptotic memory capacity of the generali...
A method to store each element of an integer-valued memory set M ⊂ {1, 2,..., K}n as a fixed point i...
WOS: A1996VL22600006This paper introduces a new family of multivalued neural networks. We have inter...
A model of neurons with CHN (Continuous Hysteresis Neurons) for the Hopfield neural networks is stud...
Das Hopfield Modell ist ein neuronales Netzwerk und kann als assoziativer Speicher genutzt werden. I...
A method to store each element of an integral memory set M subset of {1,2,...,K}(n) as a fixed point...