SOME RECENT PUBLICATIONS


1. Modeling and Realization of   Stochastic

Systems.


G. Picci: Stochastic realization of Gaussian processes Proceedings of the IEEE, Vol {64}, No. 1, pp 112-122, 1976.

 G. Picci: Some connections between the theory of sufficient statistics and the identifiability problem, SIAM Journal on Applied Mathematics, Vol {33}, No. 3, pp 383-398, 1977.

 G. Picci: On the internal structure of finite-state stochastic processes in Recent developements in Variable Structure Systems, R. Mohler and A. Ruberti eds. Springer Lecture Notes in Economics and Mathematical Systems, Vol {162}, pp. 288-304, 1978.


 A. Lindquist, G. Picci and G. Ruckebusch: On minimal splitting subspaces and Markovian representation Mathematical Systems Theory,  Vol. {12}, pp. 271-279, 1979.

 A. Lindquist and G. Picci: On the stochastic realization problem  SIAM Journal on Control and Optimization Vol. {17}, No. 3, pp. 365-389, 1979.

L. Finesso and G. Picci: A characterization of minimal square spectral factors   IEEE Transactions on Automatic Control, Vol {AC-27}, No. 1, pp. 122-127, 1982.

 A. Lindquist and G. Picci: On a condition for minimality of Markovian splitting subspaces Systems And Control Letters, Vol. {1}, No. 4, pp. 264-269, 1982.

 A. Lindquist, S. K. Mitter and G. Picci: Toward a theory of nonlinear stochastic realization in   Feedback and Control of Linear and Nonlinear Systems, D. Hinrichsen and A. Isidori eds.  Springer Lecture Notes on Control and Information Sciences, Vol {39}, pp. 175-189, 1982.

  A. Lindquist and G. Picci: Forward and backward semimartingale models for stationary increments processes  Stochastics, Vol. {15}, No. 5 ,pp. 1-50, 1985.


 A. Lindquist and G. Picci: Realization theory for multivariate stationary Gaussian processes SIAM Journal on Control and Optimization (invited paper) Vol {23}, No. 6 pp. 809-857, 1985 .


  A. Lindquist and G. Picci: A geometric approach to modeling and estimation of linear stochastic systems Journal of Math. Systems, Estimation and Control, vol.{1}, pp. 241--333, 1991.
   
   
 G. Picci: Stochastic modeling and stochastic realization theory in   Mathematical System Theory: the influence of R.E. Kalman, R.E. Kalman Festschrift, A. Antoulas eds. Springer Verlag, pp. 213--229, 1991.
 
 G. Picci and S. Pinzoni: Acausal Models and Balanced realizations of stationary processes in Linear Algebra and its Applications (special issue on Systems Theory), vol. {205-206}, pp. 957-1003, 1994.

 A. Lindquist, G. Michaletzky and G. Picci Zeros of Spectral Factors,the geometry of Splitting Subspaces and the Algebraic Riccati Inequality,   SIAM J. on Control and Optimization, vol {33}, pp. 365-401, 1995.

    G. Picci: Geometric methods in Stochastic Realization and System Identification, CWI Quarterly (invited paper), vol {9}, pp. 205-240, 1996.

A Ferrante and G. Picci, ``Minimal Realization and Dynamic Properties of Optimal Smoothers  IEEE Transactions on Automatic Control, vol. {45},  pp. 2028-2046 (2000).

   
  A. Ferrante, G. Picci, and S. Pinzoni: Silverman algorithm and the structure of discrete-time stochastic systems, Linear Algebra and its Applications (special issue on Systems and Control), vol {351-352}, pp. 219-242 (2002).

 A. Lindquist and G. Picci,   Linear Stochastic Systems: A Geometric Approach to Modeling, Estimation and Identification, Springer series in Contemporary Mathematics. Springer Verlag, 2015. The book has been translated into Chinese in 2018.


 A Ferrante and G. Picci, Representation and Factorization of Discrete-Time Rational All-Pass Functions, IEEE Transactions on Automatic Control, vol. 62, no. 7, pp. 3262-3276, DOI: 10.1109/TAC.2016.2628163 (2016).


  A. Lindquist and G. Picci: Modeling of Stationary Periodic Time Series by Bilateral  and Unilateral ARMA Representations,  in Optimization and Applications in Control and Data Science,  Springer Series in Optimization 115, pp 281-314, (2016).


 A Ferrante and G. Picci, On the state space and dynamics selection in linear stochastic models: a spectral factorization approach, IEEE Transactions on Automatic Control, vol. 64, pp. 2509-2513, (2019).


2. SISO Identification and State Space (Subspace) System  identification 


G. Picci: Some numerical aspects of multivariable system identification Mathematical Programming Studies, Vol. {18},  pp. 76-101, 1982.
   
   
A. Lindquist and G. Picci: Geometric Methods for State-Space Identification, in  Identification, Adaptation, Learning, NATO-ASI: From Identification to Learning, S. Bittanti and G. Picci. eds, Springer Verlag, pp. 1-69, 1996.

   
G. Picci and T. Katayama: Stochastic realization with exogenous inputs and subspace methods identification, Signal Processing,  special issue on subspace methods, Part II: System Identification, vol {52}, n.2, pp. 145-160, 1996.

 A. Lindquist and G. Picci, Canonical correlation analysis , approximate covariance extension and identification of stationary time-series, Automatica, vol {32}, pp. 709-733, 1996.

   
T. Katayama and G. Picci,  Realization of Stochastic Systems with Exogenous Inputs and Subspace Identification methods, Automatica, vol {35}, no. 10, pp.1635-1652, 1999.

 Chiuso, A. and Picci G.: Some Algorithmic aspects of  Subspace Identification with Inputs, Applied Mathematics and Computer Sciences, vol{11},  pp. 55-76 (2001).


 A. Chiuso and G. Picci: Asymptotic Variance of Subspace Estimates, Journal of Econometrics vol {118}, pp. 257291 (2004).



 A. Chiuso, G. Picci: On the Ill-conditioning of subspace identification with inputs Automatica, vol {40}(4), pp. 575-589 (2004). 

 A. Chiuso, G. Picci: Numerical conditioning and asymptotic variance of subspace estimates,   Automatica, vol {40}(4), pp. 677-683 (2004). 

   
A. Chiuso and  G. Picci: Subspace identification by data  orthogonalization and model decoupling,  Automatica vol {40} (4), pp. 1689-1703  (2004). 

A. Chiuso and  G. Picci: Asymptotic Variance of Subspace Methods by Data Orthogonalization and Model Decoupling: a Comparative AnalysisAutomatica, vol{40}, pp.  1705-1717 (2004).


     A. Chiuso and  G. Picci: Consistency Analysis of some Closed-loop Subspace Identification Methods, Automatica:  special issue on System Identification, vol { 41} pp. 377-391 (2005).

   
 T. Katayama, H. Kawauchi and G. Picci: Subspace Identification of Closed Loop Systems by Orthogonal Decomposition, Automatica, vol {41} pp. 863-872 (2005).

 A. Chiuso, G. Picci: Prediction Error vs. Subspace Methods in Closed Loop Identification.    Proc. of the 16th IFAC World Congress, Prague (2005).
 
A. Chiuso and G. Picci: Estimating the Asymptotic Variance of Closed-Loop Subspace Estimators, in Proc. of 14th IFAC Symposium on System Identification SYSID 2006, IFAC Papers on-Line,  pp. 1050-1055, (2006).

 M. Favaro and. G. Picci: Consistency of subspace methods for signals with almost-periodic components, Automatica,  Vol 48,   2012, Pages 514-520 (2012).

 M. Favaro and. G. Picci A subspace algorithm for extracting periodic components from multivariable signals in colored noise,   Proc 16th IFAC Symposium on System Identification (SYSID), Bruxelles, pp. 1150 -1155 (2012).

 F. Parise and  G.  Picci, Identification of high tide models in the Venetian lagoon: variable selection and G-LASSO,   Proc of the 19th IFAC World Congress, Capetown, South Africa,  pp. 10385--10390, 2014.

 G. Picci and Bin Zhu,  An Empirical Bayesian Approach to Frequency Estimation, arXiv: 1910.09475v1 [eess.SP].

 G. Picci and Bin Zhu,  Bayesian Frequency Estimation on Narrow Bands, Proceedings of the    2021 IFAC-SYSID, Padova, Italy. IFAC-PapersOnLine, 54, 7, pp. 108--113, also in arXiv: 2012.05004 (2021).

 G. Picci and Bin Zhu, Empirical Bayes Identification of Stationary Processes and Approximation of Toeplitz Spectra, Automatica, vol 142, 110362 also in arXiv: 2009.05758 (2022).

Wenqi Cao, G. Picci and A. Lindquist, Identification of low rank vector processes, Automatica (2023)


3. Factor Analysis and Errors-in-Variables Modeling


G. Picci and S. Pinzoni: Dynamic Factor-Analysis models for stationary processes IMA Journal on Mathematics of Control and Information, Vol.{3}, No. 2 , pp. 185-210, 1986.

 G. Picci: Parametrization of Factor Analysis models Journal of Econometrics, Vol. {41}, No. 1 pp. 17-38, 1989.

 G. Picci, F Gei and S. Pinzoni: Errors--in--Variables models with white measurement errors, Proc. 2nd European Control Conference (ECC), p. 2154-2158, Groningen the Netherlands, 1993.

G. Bottegal, G. Picci and S.Pinzoni On the identifiability of errors-in-variables models with white measurement errors, Automatica, vol {47}  pp. 545—551, (2011).


 G. Bottegal and G. Picci: A note on Generalized Factor Analysis models,   Proc. 50th Decision and Control  Conference (CDC), pp. 1485-1490, Orlando FLA, USA (2011).

  G. Picci and G. Bottegal: Generalized Factor Analysis Models, in    Control Theory: Mathematical Perspectives on Complex Networked System, Frank Allg{\"o}wer, Vincent Blondel, Uwe Helmke Eds,  Mathematisches Forschungsinstitute Oberwolfach, Oberwolfach, Germany, pp. 705-706, doi=  10.4171/OWR/2012/12 (2012).

 G. Bottegal and G.  Picci: Modeling random flocks through Generalized Factor Analysis, Proc. of the European Control Conference ECC13,  Z\"urich, pp. 2421—2426 (2013).

 G. Bottegal and G.  Picci: Analysis and identification of  complex stochastic systems admitting a flocking structure, Proc of the 19th IFAC World Congres, Capetown, South Africa, pp. 2323-2328 (2014).

 G. Bottegal and G.  Picci, Modeling complex systems by Generalized Factor Analysis, IEEE Transactions on Automatic Control, vol {60}: pp 759 - 774, doi: 10.1109/TAC.2014.2357913, (2015).

  G. Picci, L. Falcon, A. Ferrante and M. Zorzi,  Hidden Factor estimation in Dynamic Generalized Factor Analysis Models, Automatica, (2023).


4. Stochastic model reduction by aggregation


  G.Picci: Application of stochastic realization theory to a fundamental  problem of statistical physics (invited keynote address at MTNS-85) in Modelling, Identification and Robust Control, C. I.  Byrnes, A. Lindquist eds.  North Holland, pp. 211-258 (1986).

  G. Picci: Aggregation of linear systems in a completely deterministic framework in   Three Decades of Mathematical System Theory. A Collection  of Surveys at the Occasion of the Fiftieth Birthday of Jan C. Willems,  H. Neijmeijer, J.M. Schumacher eds., Springer Lecture Notes in Control and Information Sciences, Vol.{135} pp. 358-381, 1989.

  G.Picci: Stochastic model reduction by aggregation in   Systems Models and Feedback: Theory and Applicatons, A Isidori, T.J. Tarn eds., Progress in Systems and Control Theory (PSCT), volume 12, Birkhauser, 1992.

G. Picci and T.S.J. Taylor: Generation of Gaussian Processes and Linear Chaos. Proc 31st IEEE Conf. on Decision and Control, Tucson Arizona, pp. 2125--2131, 1992.

G. Picci and T.S.J. Taylor: Stochastic aggregation of flexible mechanical structures in   Recent advances in Mathematical Theory of Systems, Control, Networks and Signal Processing II, H. Kimura, S. Kodama eds., pp. 203--207, Mita press, Tokyo, 1992.

 G. Picci: Markovian representation of linear Hamiltonian systems, in Probabilistic Methods in Mathematical Physics, F. Guerra, M.I. Loffredo and C. Marchioro eds. World Scientific Singapore,  pp.358--373, 1992.


 

5.  Stochastic Control and applications


 G.B. Di Masi, L. Finesso and G. Picci: Design of an LQG controller for single-point moored large tankers, Automatica, Vol.{22}, No. 2, pp. 155-169, 1986.
   
G. Picci and S. Pinzoni: On feedback-dissipative systems Journal of Math. Systems, Estimation and Control, vol.{2}, No. 1, pp. 1--30, 1992.


R. Muradore and  G. Picci: Mixed H^2 / H^{infty} control: the discrete-time case, Systems and Control Letters, vol {54}, pp. 1-13 (2005).

G. Picci and T.J. Taylor: Almost sure exponential convergence of random gossip algorithms, Internat. J. of Robust and Nonlinear Control vol 33 pp. 1033-1045 (2012)

6.  Covariance Extension and applications


 F. Carli, A. Ferrante, M. Pavon and  G. Picci:  A Maximum Entropy solution of the Covariance Selection Problem for Reciprocal Processes. In:   Three Decades of Progress in Control Sciences, Hu, X.; Jonsson, U.; Wahlberg, B.; Ghosh, B. (Eds.) p. 77-93, Springer-Verlag, ISBN: 978-3-642-11277-5 (2010).

 F. Carli, A. Ferrante, M. Pavon and  G. Picci :  A Maximum Entropy approach to the Covariance Extension Problem for Reciprocal Processes, in Proc. of the19th Int. Symposium on the Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary, pp. 899-903, (2010).

 F. Carli and  G. Picci: On the factorization  approach to band extension of block-circulant matrices, in Proc. of the19th Int. Symposium on the Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary, pp. 907-914, (2010).

 F. Carli, A. Ferrante, M. Pavon and  G. Picci: A Maximum Entropy approach to the Covariance Extension Problem for Reciprocal Processes, IEEE Transactions on Automatic Control, vol {56}: pp. 1999--2012, (2011).

 F. Carli, A. Ferrante, M. Pavon and  G. Picci: An Efficient Algorithm for Dempster's Completion of Block--Circulant Covariance Matrices, Proc. 50th Decision and Control  Conference (CDC}, pp. 2963--2968, Orlando FLA, USA (2011),.

 A. Lindquist and G. Picci, The Circulant Rational Covariance Extension Problem: The Complete Solution, IEEE Transactions on Automatic Control, vol (58}, pp 2848-2861 (2013).

 F. Carli, A. Ferrante, M. Pavon and  G. Picci: An Efficient Algorithm for Maximum--Entropy Extension of Block--Circulant Covariance Matrices, Linear Algebra and its Applications, vol { 439} pp 2309--2339, doi: 10.1016  j.laa.2013.06.014 (2013).

 A.Lindquist, C. Masiero and G.  Picci, On the Multivariate Circulant Rational Covariance Extension Problem, Proc of the 2013 Decision and Control Conference, Florence, Italy, pp. 7155—7161 (2013).

 G. Picci, A new approach to circulant band extension, Proc of the 22nd  Int. Symposium on the Mathematical Theory of Networks and Systems (MTNS 2016), Minneapolis, MN. pp 123-130 (2016).

G. Picci and Bin Zhu: Approximation of Vector Processes by Covariance Matching with Applications to Smoothing, IEEE Control Systems Letters, vol 1 pp. 200-205,  (2017).

Bin Zhu and G. Picci, Proof of Local Convergence of a new Algorithm for Covariance Matching of  Periodic ARMA Models,  IEEE Control Systems Letters, vol 1 pp. 206-211,  (2017).

G. Picci: Periodic vector processes with an internal reciprocal dynamics System and Control Letters (The Art Krener spcial Issue) to appear.







7. Vision-Based estimation and guidance


R.Frezza, G. Picci, P. Perona, S. Soatto: System Theoretic Aspects of Dynamic Vision (invited paper), in Trends in Control, A. Isidori ed. Springer Verlag, pp. 349 - 383 , (1995).

   
R.Frezza, G. Picci: On line path following by recursive spline updating", (invited paper FP09)   Proceedings of the 34th Conference on Decision and Control, New Orleans, IEEE Press, pp. 4047-4052, vol {4}, (1995).

   
 G. Picci: Dynamic Vision and Estimation on Spheres, Proceedings of the 1997 Conference on Decision and Control, San Diego Ca., p. 1140-1145, IEEE Press (1997).
   
R.Frezza, S. Soatto, G. Picci: On-line path following by recursive spline updating, Proceedings of the 1997 Conference on Decision and Control, San
Diego Ca,  p. 1130-1135, IEEE Press, (1997).

A. Chiuso and G. Picci: Visual Tracking of Points as Estimation  onthe Unit  Sphere in The Confluence of Vision and Control, D. Kriegman, G. Hagerand S. Morse eds. Springer-Verlag  Lecture Notes in Control and Information Systems (LNCIS) n. 237, pp. 90-105, (1998).

R Frezza, G. Picci and S. Soatto ``A Lagrangian Formulation of Nonholonomic Path Following" in The Confluence of Vision and Control, D. Kriegman, G. Hager and S. Morse eds. Springer-Verlag Lecture Notes in Control and Information Systems (LNCIS) n. 237, pp.118-133, (1998).

A. Chiuso and G. Picci: A wide-sense estimation theory on the unit sphere, in Proceedings of the 1998 Conference on Decision and Control, Tampa,
Florida, paper n. FM02-5, p. 3745-3750, (1998).

 
A. Chiuso, A. Ferrante, G. Picci: Reciprocal realization  and modeling of textured images, Proc. of the CDC-ECC05, conference, Sevilla, Spain, pp. 6059-6064, (2005).

A. Chiuso, G. Picci and S. Soatto: Wide sense estimation on the orthogonal group, Communications in Information and Systems (the Brockett legacy special issue) vol {8}, pp. 185-200, (2008).

A. Chiuso and  G. Picci: Some identification techniques in computer vision (invited paper), in Proc. of the 47th IEEE Decision and Control Conference, pp. 3935-3946, Cancun, Mex. (2008).






8. Identification of Mechanical Systems via Variational Integrators


 M. Bruschetta, G. Picci and A. Saccon: Discrete Mechanical Systems: Second Order Modelling and  Identification, Proc of the 15th IFAC Sysmposium on System Identification (SYSID), St Malo, France, pp. 456-461,  (2009).

 M. Bruschetta, G. Picci and A. Saccon : How to sample a linear mechanical system, in Perspectives in Mathematical System Theory, Control, and Signal Processing, J.C. Willems, S. Hara, Y. Ohta and H. Fujioka eds, Springer LNCIS series n. 398, pp 343-354 (2010).

 M. Bruschetta, G. Picci and A. Saccon: A variational integrators approach to second order modeling and identification of linear mechanical systems, Automatica, vol {50}, pp. 727 -- 736, (2013).