Particles encountered in nature and engineering practice are normally not spherical but of
irregular shapes. Particle shape plays a key role in determining the behaviour of bulk solids …

Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable
efficiency–as though these inferences were a reflexive response of their cognitive …

Chaos in science has always been a fascinating realm since it challenges the usual
scientific approach of reductionism. While carefully distinguishing between complexity …

In 1981 I started a simulation of a model consisting of a chain of logistic maps coupled to
their neighbors and with parameters in the regions of chaotic behavior_ Soon r realized that …

First, a neural network model as the globally coupled map (GCM) is proposed. The model is
obtained by modification of a Hopfield network model that has a negative self‐feedback …

We report experimental realization of high-dimensional chaos in a semiconductor laser with
delayed feedback from a T-shaped cavity. We study the transition phenomena from regular …

Numerical investigation of a single layer recurrent neural network model in which the
synaptic connection matrix is formed by summing direct products of succesive patterns in …

Complex dynamics is expected to enable us to avoid combinatorial explosion and diverging
program complexity that has been one of the essential difficulties in solving complex …

In solving optimization problems by the neural network models (the Hopfield model and the
Boltzmann machine, etc.), a serious problem is that the existence of a huge number of local …

Since deterministic chaos is not only a profound concept in science but also a ubiquitous
phenomenon in real-world nonlinear systems, extending to a variety of temporal and spatial …