AbstructIn rule-based artificial intelligence (AI) planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some “working memory.” Normally, the intent is to determine which rules are relevant to the current situation (i.e., to find the “conflict set”). The traditional approach to solve such a “match phase ...

While finite cop-win finite graphs possess a good structural characterization, none is known for infinite cop-win graphs. As evidence that such a characterization might not exist, we provide as large as possible classes of infinite graphs with finite cop number. More precisely, for each infinite cardinal and each positive integer k, we construct 2 non-isomorphic k-cop-win graphs satisfying addi...

A (1,-1)-matrix will be called a bent type matrix if each row and each column are bent sequences. A similar description can be found in Carlisle M. in which the authors use the properties of bent type matrices to construct a class of bent functions. In this paper we give a general method to construct bent type matrices and show that the bent sequence obtained from a bent type matrix is a genera...

In the current Modelica specification, the only admitted external entities are memory-less functions. We propose an extension to allow parts of the model containing internal states, conditioning and discrete dynamics, to be definable as external functions. This opens the door to separate compilation of Modelica code. For this purpose, we introduce the language construct switchwhen and the type ...

BACKGROUND For bioanalytical systems sensitivity and biomolecule activity are critical issues. The immobilization of proteins into multilayer systems by the layer-by-layer deposition has become one of the favorite methods with this respect. Moreover, the combination of nanoparticles with biomolecules on electrodes is a matter of particular interest since several examples with high activities an...

This paper 1 proposes a method to extract nonlinear discriminant features from given input measurements by using outputs of multilayer Perceptron (MLP). Linear Discriminant Analysis (LDA) is one of the best known methods to construct linear features which are suitable for class discrimination. Otsu showed that LDA can be extended to nonlinear if we can estimate Bayesian a posteriori probabiliti...

In this paper two types of neural networks, namely the “traditional” tansig based neural networks and the multilayer perceptrons based on fuzzy flipflops (FNN) trained by the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM) are tested and compared on their robustness to test functions outliers. The robust design of the FNN is presented, and the best suitable fuzzy neuro...

In this paper, we show a scheme for recognition of handwritten and printed numerals using a multilayer and clustered neural network trained with the backpropagation algorithm. Kirsch masks are adopted for extracting feature vectors and a three-layer clustered neural network with five independent subnetworks is developed for classifying numerals efficiently. The neural network was trainned with ...

The choice of architecture of artificial neuron network (ANN) is still a challenging task that users face every time. It greatly affects the accuracy of the built network. In fact there is no optimal method that is applicable to various implementations at the same time. In this paper we propose a method to construct ANN based on clustering, that resolves the problems of random and ad’hoc approa...