Titlebook: Neural Nets; 13th Italian Worksho Maria Marinaro,Roberto Tagliaferri Conference proceedings 2002 Springer-Verlag Berlin Heidelberg 2002 Ada

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A Comparison of Signal Compression Methods by Sparse Solution of Linear Systemsnary. The compression is obtained by selecting a few elements of the dictionary for the expansion. Therefore, signal description is realized by specifying the selected elements of the dictionary as well as their coefficients in the linear expansion. A crucial issue in this approach is the algorithm

傷心

Fuzzy Time Series for Forecasting Pollutants Concentration in the Airnymous strait. Consequently, the crossing and heavy vehicular traffic discharges organic and inorganic compounds in the urban atmosphere that can affect the health of citizens. In this paper, a design of a prediction system for pollutants concentration in the urban atmosphere is proposed. In this st

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Terminal

Sound Synthesis by Flexible Activation Function Recurrent Neural Networksed on a learning from examples strategy (in particular in this paper we study single-reed woodwind instruments). It is well known that one of the main problems in physical modeling concerns the difficulty of parameter identification and the definition of the exciter nonlinear function shape (which p

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Spline Recurrent Neural Networks for Quad-Tree Video Codingove the generalization performance, a flexible spline-based activation function, suitable for signal processing applications, has been used. Preliminary experimental results show that the proposed approach represents a viable alternative with respect to existing standards for high-quality video compression.

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A New Approach to Detection of Muscle Activation by Independent Component Analysis and Wavelet Trans (surface EMG) signals; source separation is performed by a neural net-work that implements on Independent Component Analysis algorithm. In this way we obtain a signal set each representing single muscle activity. The wave-let transform, lastly, is utilised to detect muscle activation intervals.