Titlebook: Neural Nets; 16th Italian Worksho Bruno Apolloni,Maria Marinaro,Roberto Tagliaferri Conference proceedings 2006 Springer-Verlag Berlin Heid

Inelasticity

A System for Transmitting a Coherent Burst of Activity Through a Network of Spiking Neuronsons. For our convenience we use a spiking model that is has an intrinsic delay between an input and output spike. We look at issues involving transmission of a desired average level of stable spiking activity over many layers, and show how feed-back reset inhibition can achieve this aim. We then dea

單調(diào)女

NEC: A Hierarchical Agglomerative Clustering Based on Fisher and Negentropy Informationgorithm is based on a competitive Neural Network or on a Probabilistic Principal Surfaces approach and the second one on an agglomerative clustering based on both Fisher and Negentropy information. Different definitions of Negentropy information are used and some tests on complex synthetic data are

譏笑

A Recurrent ICA Approach to a Novel BSS Convolutive Nonlinear Problem algorithm performs the separation after the convolutive mixing of post nonlinear convolutive mixtures. The recurrent neural network produces the separation by minimizing the output mutual information. Experimental results are described to show the effectiveness of the proposed technique.

法律的瑕疵

RALES

Nonlinear Exploratory Data Analysis Applied to Seismic Signalsear Component Analysis (CCA), which are both nonlinear. Performance comparison of the three methods is made on a set of seismic data recorded on Stromboli that includes three classes of signals: explosion-quakes, landslides, and microtremors. The unsupervised analysis of the signals is able to disco

dura-mater

Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter main advantage of this method is that it encompasses the characteristics of WT and ICA. In order to show the novelty of our method, we present a biomedical signal processing application in which ICA has poor performances, whereas WICA yields good results. In particular, we discuss the artifact canc

Grasping

Indicative

Short Term Local Meteorological Forecasting Using Type-2 Fuzzy Systemsgeographical region and by studying their evolution, thus foreseeing the meteorological situation in a certain place. In this paper a “l(fā)ocal level” approach, based on time series forecasting using Type-2 Fuzzy Systems, is proposed. In particular temperature forecasting is inspected. The Fuzzy System

Canopy

Learning and Data Driver Methods for Short Term Meteo Forecastal variables and the occurrence of particular phenomena such as rain and road ice. The meteorological variables forecast system is based on a recurrent feed forward multi layer perceptron which make the forecasts using data coming from synoptic electronic sensors. Road ice is forecasted using an ana

Dorsal-Kyphosis