Visual perception is typically performed in the context of a task or goal. Nonetheless, visual processing has traditionally been conceptualized in terms of a fixed, task-independe...
We consider spiking neural P systems with rules allowed to introduce zero, one, or more spikes at the same time. The motivation comes both from constructing small universal systems...
Haiming Chen, Mihai Ionescu, Tseren-Onolt Ishdorj,...
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley 1] as a fractal image compression ...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
: This paper describes a system, which integrates Neural Network (NN) models into adaptation circle of Case-based Reasoning (CBR) system. Neural Network supported adaptation can pr...
This paper reports the results of experiments in complex Arabic phonetic features identification using a rulebased system (SARPH) and modular connectionist architectures. The firs...
In this paper a new approach for approximation problems involving only few input and output parameters is presented and compared to traditional Backpropagation Neural Networks (BP...
A system based on the charge-discharge characteristics of the neural synapses of the visual path, is shortly introduced. The proposed system uses the LSR (length/speed ratio) descr...
Many processes are composed of a n-fold repetition of some simpler process. If the whole process can be modeled with a neural network, we present a method to derive a model of the...