Search Results - "Soverini, U."

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  1. 1

    Speech Enhancement Combining Optimal Smoothing and Errors-In-Variables Identification of Noisy AR Processes by Bobillet, W., Diversi, R., Grivel, E., Guidorzi, R., Najim, M., Soverini, U.

    Published in IEEE transactions on signal processing (01-12-2007)
    “…In the framework of speech enhancement, several parametric approaches based on an a priori model for a speech signal have been proposed. When using an…”
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    Journal Article
  2. 2

    Kalman filtering in extended noise environments by Diversi, R., Guidorzi, R., Soverini, U.

    Published in IEEE transactions on automatic control (01-09-2005)
    “…This note introduces an extended environment for Kalman filtering that considers also the presence of additive noise on input observations in order to solve…”
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    Journal Article
  3. 3

    Identification of dynamic errors-in-variables models by Castaldi, P., Soverini, U.

    Published in Automatica (Oxford) (01-04-1996)
    “…This paper deals with the identifiability of scalar dynamic errors-in-variables models characterized by rational spectra. The hypothesis of causality for the…”
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    Journal Article
  4. 4

    Perspectives on errors-in-variables estimation for dynamic systems by Söderström, Torsten, Soverini, Umberto, Mahata, Kaushik

    Published in Signal processing (01-08-2002)
    “…The paper gives an overview of various methods for identifying dynamic errors-in-variables systems. Several approaches are classified by how the original…”
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    Journal Article
  5. 5

    A comparison among different inversion methods for multi-exponential NMR relaxation data by Borgia, G C, Bortolotti, V, Brown, R J, Castaldi, P, Fantazzini, P, Soverini, U

    Published in Magnetic resonance imaging (1994)
    “…The inversion of data to be represented by sums or continuous distributions of exponentials is done by different algorithms and compared. The published CONTIN…”
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    Journal Article
  6. 6

    Optimal errors-in-variables filtering by Guidorzi, Roberto, Diversi, Roberto, Soverini, Umberto

    Published in Automatica (Oxford) (01-02-2003)
    “…This paper deals with optimal (minimal variance) filtering in an errors-in-variables framework. Differently from many other contexts, errors-in-variables…”
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    Journal Article
  7. 7

    Identification of dynamic errors-in-variables models: Approaches based on two-dimensional ARMA modeling of the data by Söderström, Torsten, Mahata, Kaushik, Soverini, Umberto

    Published in Automatica (Oxford) (01-05-2003)
    “…In this paper we propose a parametric and a non-parametric identification algorithm for dynamic errors-in-variables model. We show that the two-dimensional…”
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    Journal Article
  8. 8

    Robust residual generation for dynamic processes using de-coupling technique by Diversi, R., Simani, S., Soverini, U.

    “…The work presents some results concerning robust fault detection for dynamic processes using a disturbance decoupling technique. The first step of the approach…”
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    Conference Proceeding
  9. 9

    Blind identification and equalization of two-channel FIR systems in unbalanced noise environments by Diversi, Roberto, Guidorzi, Roberto, Soverini, Umberto

    Published in Signal processing (2005)
    “…Blind identification is a very significant problem in many contexts where only the output of transmission channels can be observed. The solutions that can be…”
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    Journal Article
  10. 10

    Algorithms for optimal errors-in-variables filtering by Diversi, Roberto, Guidorzi, Roberto, Soverini, Umberto

    Published in Systems & control letters (15-01-2003)
    “…This paper introduces a new algorithm for optimal filtering of data generated by errors-in-variables processes and compares its efficiency with that of two…”
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    Journal Article
  11. 11

    Identification of static errors-in-variables models: the rank reducibility problem by Soverini, Umberto, Beghelli, Sergio

    Published in Automatica (Oxford) (01-07-2001)
    “…The problem of identifying linear static relations from noisy data is investigated under the assumptions of the Frisch scheme. The work presents an attempt to…”
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    Journal Article
  12. 12

    Identification of multivariable errors-in-variables models by Castaldi, P., Diversi, R., Guidorzi, R., Soverini, U.

    Published in 1999 European Control Conference (ECC) (01-08-1999)
    “…The paper deals with a new identification approach, based on a prediction error method, for multivariable errors-in-variables models (EIV). Starting from the…”
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    Conference Proceeding
  13. 13

    A new approach for identifying noisy input-output FIR models by Diversi, R., Guidorzi, R., Soverini, U.

    “…This paper proposes an efficient algorithm for identifying FIR models when also the input is assumed as affected by additive noise. This procedure is more…”
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    Conference Proceeding
  14. 14

    A noise-compensated estimation scheme for AR processes by Diversi, R., Guidorzi, R., Soverini, U.

    “…This paper deals with the problem of identifying autoregressive models in presence of additive measurement noise. A new approach, based on some theoretical…”
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    Conference Proceeding
  15. 15

    A frequential approach for errors-in-variables models by Beghelli, S., Castaldi, P., Soverini, U.

    Published in 1997 European Control Conference (ECC) (01-07-1997)
    “…This paper presents an identification method for errors-in-variables systems with input-output measurements affected by white and mutually correlated noises…”
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    Conference Proceeding
  16. 16

    Identification of residual generators for fault detection of linear dynamic models by Simani, S., Diversi, R., Soverini, U.

    “…Classical model-based fault detection schemes for linear multivariable systems require the definition of suitable residual functions. This paper shows the…”
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    Conference Proceeding
  17. 17

    WWW implementation of an identification course: structure and users' evaluation by Guidorzi, R.P., Soverini, U., Castaldi, P., Diversi, R.

    “…This paper describes the structure of the course Dynamic System Identification that has been designed as an experimental multicampus solution, based on Web…”
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    Conference Proceeding