A layered neural network with three-state neurons optimizing the mutual information
نویسندگان
چکیده
The time evolution of an exactly solvable layered feedforward neural network with three-state neurons and optimizing the mutual information is studied for arbitrary synaptic noise (temperature). Detailed stationary temperature-capacity and capacity-activity phase diagrams are obtained. The model exhibits pattern retrieval, pattern-fluctuation retrieval and spin-glass phases. It is found that there is an improved performance in the form of both a larger critical capacity and information content compared with three-state Ising-type layered network models. Flow diagrams reveal that saddle-point solutions associated with fluctuation overlaps slow down considerably the flow of the network states towards the stable fixed-points.
منابع مشابه
Reconstruction of the neural network model of motor control for virtual C.elegans on the basis of actual organism information
Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...
متن کاملAn optimal Q-state neural network using mutual information
Starting from the mutual information we present a method in order to find a hamiltonian for a fully connected neural network model with an arbitrary, finite number of neuron states, Q. For small initial correlations between the neurons and the patterns it leads to optimal retrieval performance. For binary neurons, Q = 2, and biased patterns we recover the Hopfield model. For three-state neurons...
متن کاملApplication of Artificial Neural Network in Study Phenomenon of Landslide and Risk Modeling using Geographic Information System (GIS), Case Study: Alamoot Rood Watershed
One of the natural disasters that occurs in abundance in Iran, due to the geological structure, morphological and seismic conditions, and damages the lives and property of people is a landslide. Roodbar Alamoot watershed in the east of Qazvin province is a mountainous region with a high potential for occurrence of landslides. Because of their active status, there is also a growing trend of...
متن کاملNeural Network Modelling of Optimal Robot Movement Using Branch and Bound Tree
In this paper a discrete competitive neural network is introduced to calculate the optimal robot arm movements for processing a considered commitment of tasks, using the branch and bound methodology. A special method based on the branch and bound methodology, modified with a travelling path for adapting in the neural network, is introduced. The main neural network of the system consists of diff...
متن کاملHammerstein-Wiener Model: A New Approach to the Estimation of Formal Neural Information
A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of inp...
متن کامل