Self-organization of Multiple Winner-take-all Neural Networks
نویسنده
چکیده
In this paper, analysis of the information content of discretely ring neurons in unsupervised neural networks is presented, where information is measured according to the network's ability to reconstruct its input from its output with minimum mean square Euclidean error. It is shown how this type of network can self-organise into multiple winner-take-all subnetworks, each of which tackles only a low-dimensional subspace of the input vector. This is a rudimentary example of a neural network that e ectively subdivides a task into manageable subtasks.
منابع مشابه
Winner-Take-All Discrete Recurrent Neural Networks
This paper proposes a discrete recurrent neural network model to implement winner-take-all function. This network model has simple organizations and clear dynamic behaviours. The dynamic properties of the proposed winner-take-all networks are studied in detail. Simulation results are given to show network performance. Since the network model is formulated as discrete time systems , it has advan...
متن کاملAdaptive perceptual pattern recognition by self-organizing neural networks: Context, uncertainty, multiplicity, and scale
| A new context-sensitive neural network, called an \EXIN" (excitatory+inhibitory) network, is described. EXIN networks self-organize in complex perceptual environments, in the presence of multiple superimposed patterns, multiple scales, and uncertainty. The networks use a new inhibitory learning rule, in addition to an excitatory learning rule, to allow superposition of multiple simultaneous n...
متن کاملAnalysis for a class of winner-take-all model
Recently we have proposed a simple circuit of winner-take-all (WTA) neural network. Assuming no external input, we have derived an analytic equation for its network response time. In this paper, we further analyze the network response time for a class of winner-take-all circuits involving self-decay and show that the network response time of such a class of WTA is the same as that of the simple...
متن کاملSelf-organized annealing in laterally inhibited neural networks shows power law decay
In this paper we present a method which assigns to each layer of a multilayer neural network, whose network dynamics is governed by a noisy winner-take-all mechanism, an approximated temperature β. This approximated temperature is obtained by comparison of a softmax mechanism where a temperature is well defined with the noisy winner-take-all mechanism. We apply this method to a multilayer neura...
متن کاملA Fast Winner-Take-All Neural Networks With the Dynamic Ratio
In this paper, we propose a fast winner-take-all (WTA) neural network. The fast winner-take-all neural network with the dynamic ratio in mutual-inhibition is developed from the general mean-based neural network (GEMNET), which adopts the mean of the active neurons as the threshold of mutual inhibition. Furthermore, the other winner-take-all neural network enhances the convergence speed to becom...
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:
- Connect. Sci.
دوره 9 شماره
صفحات -
تاریخ انتشار 1997