Le recueil de données diverses issues de l'imagerie, de compétences expertes ou de signaux physiologiques est devenu courant pour l'étude d'une pathologie donnée. Leur exploitation est effectuée par le clinicien qui les analyse et les agrège en fonction de ses connaissances. La motivation de ce travail est de modéliser ce processus d'agrégation à l...
We present an original initialization procedure for the parameters of feedforward wavelet networks, prior to training by gradient-based techniques. It takes advantage of wavelet frames stemming from the discrete wavelet transform, and uses a selection method to determine a set of best wavelets whose centers and dilation parameters are used as initi...
This paper concerns finding the `optimal' number of (non-overlapping) word groups for text classification. We present a method to select which words to cluster in word groups and how many such word groups to use on the basis of a set of pre-classified texts. The method involves a `greedy' search through the space of possible word groups. The words ...
Cette thèse concerne l'apprentissage de règles relationnelles à partir d'exemples et de contre-exemples, à l'aide d'algorithmes évolutionnaires. Nous étudions tout d'abord un biais de langage offrant une expressivité suffisamment riche pour permettre de couvrir à la fois le cadre de l'apprentissage relationnel par interprétations et les formalismes...
A methodology is proposed for the extraction of local trends from a time-series. It has been designed to suit the needs of interpretation-oriented visualization from raw data. After giving implementation details for efficient computation of local trends, a characteristic analysis span is determined for each time-series. The processing results in a ...
We present the global k-means algorithm which is an incremental approach to clustering that dynamically adds one cluster at a time through a deterministic global search procedure consisting of N (with N being the size of the data set) executions of the k-means algorithm from suitable initial positions. We also propose modifications of the methods t...
Published in Studies in health technology and informatics
The accumulation of several data coming from medical images and signals, expert knowledge and databases is becoming very common for the study of a given pathology. The aggregation of all this information is mentally performed by a clinician, and generally allows for a better medical decision in clinical studies. We propose in this article a fusion ...
This work deals with fault detection and isolation (FDI) of an induction motor. Its supervision cannot be performed on the sole knowledge of analytical redundancy relations : a normal functioning state of the motor and a speed-sensor failure state cannot be distinguished from a behavioral analytical model. A solution is proposed using two inductive...
This paper presents an approach to score following. The real-time alignment of a performance with a score is obtained through the use of a hidden Markov model. The model works on two levels. The lower level compares the features of the incoming signal with the expected ones. Groups of states of the lower level are embedded in states at the higher l...
In this paper, we propose an evolutionary point of view on organization in multi-agent systems, in which the MAS is seen as an ecosystem. This indeed addresses the issue of the design of evolvable agent behaviors. We introduce therefore, through the concept of Ethogenetics, some important design principles that are not fulfilled by classical evolut...
