Artificial Neural Network Model for prediction of time-series data is revisited on analysis of the Indonesian stock-exchange data. We introduce the use of Multi-Layer Perceptron to percept the modified Poincare map of the given financial time-series data. The modified Poincare map is believed to...

We present a computational model to study the robustness and degradation of dynamics on a network that includes a large number of units and connections between them. Each unit has an internal structure and it is connected to other units through contact points. These contact points correspond to...

This paper reported multiple induction of spiral waves with a stochastic signal in a square lattice network model composed of type I Morris–Lecar (ML) neurons, where each neuron is coupled to its four nearest neighbors. The induction occurs in two or three distinct regions of noise intensity,...

In this paper we try to bridge breakthroughs in quantitative sociology/econometrics, pioneered during the last decades by Mac Fadden, Brock–Durlauf, Granovetter and Watts–Strogatz, by introducing a minimal model able to reproduce essentially all the features of social behavior highlighted by...

A neuron, the fundamental element of neural systems, interacts with other neurons, often producing very complicated behavior. To analyze, model, or predict such complicated behavior, it is important to understand how neurons are connected as well as how they behave. In this paper, we propose two...

We propose a dynamic packet routing strategy by using neural networks on scale-free networks. In this strategy, in order to determine the nodes to which the packets should be transmitted, we use path lengths to the destinations of the packets, and adjust the connection weights of the neural...

In this paper, the storage capacity of the Q-state complex phasor neural network is analysed with the signal-to-noise theory. The results indicate that the storage capacity of the model approaches that of the Hopfield model if the number Q is small; while the storage capacity is proportional to...

The phenomenon of stochastic resonance (SR) is reported in a completely noise-free situation, with the role of thermal noise being taken by low-dimensional chaos. A one-dimensional, piecewise linear map and a pair of coupled excitatory-inhibitory neurons are the systems used for the...

We investigate storage capacity of a fully connected layered neural network with Q(⩾2)-states clock neurons, including Q=∞ (corresponding to oscillatory neurons) and with intra-layer connections, where random Q-values patterns are embedded into the network by the Hebbian learning rule. We...

We study general phase structures of neural-network models that have Z(2) local gauge symmetry. The Z(2) spin variable Si=±1 on the i-th site describes a neuron state as in the Hopfield model, and the Z(2) gauge variable Jij=±1 describes a state of the synaptic connection between j-th and i-th...