Pii: S0893-6080(98)00136-1
نویسندگان
چکیده
A neural network is considered which is designed as a system of phase oscillators and contains a central oscillator that interacts with a number of peripheral oscillators. Analytical and simulation methods are used to study the dynamics of the system that is conditioned by the interaction parameters and natural frequencies of the oscillators. The boundaries of parameter regions are found that correspond to the synchronization of the whole network or to partial synchronization between the central oscillator and a group of peripheral oscillators. For a system with two peripheral oscillators the bifurcation analysis is applied to describe the changes of synchronization modes. The implications of the results for attention modeling are discussed. q 1999 Elsevier Science Ltd. All rights reserved.
منابع مشابه
Analyzing stability of equilibrium points in neural networks: a general approach
Networks of coupled neural systems represent an important class of models in computational neuroscience. In some applications it is required that equilibrium points in these networks remain stable under parameter variations. Here we present a general methodology to yield explicit constraints on the coupling strengths to ensure the stability of the equilibrium point. Two models of coupled excita...
متن کاملExplanation of the "virtual input" phenomenon
We write this letter to comment on the "virtual input" phenomenon reported by Thaler (Neural Networks, 8(1) (1995) 55-65). The author attributed the phenomenon to the network's ability to perform pattern classification and completion, and reported that pruning probability affects the number of virtual inputs observed. Our independent study of Thaler's results, however, reveals a simpler explana...
متن کاملParallel and robust skeletonization built on self-organizing elements
A massively parallel neural architecture is suggested for the approximate computation of the skeleton of a planar shape. Numerical examples demonstrate the robustness of the method. The architecture is constructed from self-organizing elements that allow the extension of the concept of skeletonization to areas remote to image processing.
متن کاملInformation storage capacity of incompletely connected associative memories
In this paper, the memory capacity of incompletely connected associative memories is investigated. First, the capacity is derived for memories with fixed parameters. Optimization of the parameters yields a maximum capacity between 0.53 and 0.69 for hetero-association and half of it for autoassociation improving previously reported results. The maximum capacity grows with increasing connectivity...
متن کاملPii: S0893-6080(98)00064-1
A recurrent neural network can possess multiple stable states, a property that many brain theories have implicated in learning and memory. There is good evidence for such multistability in the brainstem neural network that controls eye position. Because the stable states are arranged in a continuous dynamical attractor, the network can store a memory of eye position with analog neural encoding....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999