By Professor Prof. V. Solo

Book Chapters

Solo V, 2016, '’unobserved’ monte carlo methods for adaptive algorithms', in Modeling Uncertainty : An Examination of Stochastic Theory, Methods, and Applications, pp. 373 - 382

Solo V, 2013, 'Averaging analysis of adaptive algorithms made simple', in System Identification Environmental Modelling and Control System Design, pp. 115 - 131, http://dx.doi.org/10.1007/978-0-85729-974-1_6

Solo V, 2012, 'Averaging analysis of adaptive algorithms made simple', in System Identification Environmental Modelling and Control System Design, pp. 115 - 131, http://dx.doi.org/10.1007/978-0-85729-974-1_6

Solo V, 2012, 'Averaging Analysis of Adaptive Algorithms Made Simple', in Wag L; Garnier H (ed.), System Identification, Environmental Modelling, and Control System Design, Springer, New York, pp. 123 - 138, http://dx.doi.org/10.1007/978-0-85729-974-1

Brown EN; Solo V; Choe Y; Zhang Z, 2004, 'Measuring Period of Human Biological Clock: Infill Asymptotic Analysis of Harmonic Regression Parameter Estimates', in Numerical Computer Methods, Part D, Elsevier, pp. 382 - 405, http://dx.doi.org/10.1016/s0076-6879(04)83016-7

Solo V, 2001, 'The end of time series', in Statistics in the 21st Century, pp. 444 - 450

Solo V, 1995, 'Averaging Methods for the Analysis of Adaptive Algorithms', in The IMA Volumes in Mathematics and its Applications, Springer New York, pp. 351 - 358, http://dx.doi.org/10.1007/978-1-4419-8568-2_16

Solo V, 1981, 'Time Series Recursions and Self-Tuning Control', in Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, Springer US, pp. 178 - 184, http://dx.doi.org/10.1007/978-1-4613-9464-8_26

Solo V, 'Stability of slowly time-varying linear systems', in Lecture Notes in Control and Information Sciences, Springer Berlin Heidelberg, pp. 451 - 456, http://dx.doi.org/10.1007/bfb0113260

Journal articles

Yue Z; Wang X; Solo V, 2026, 'A system identification approach to clustering autoregressive vector time series', Automatica, 193, http://dx.doi.org/10.1016/j.automatica.2026.113183

Wang X; Solo V, 2026, 'Geometry-preserving numerical scheme for Riemannian stochastic differential equations', Automatica, 190, http://dx.doi.org/10.1016/j.automatica.2026.113048

Solo V, 2025, 'Asymptotic Analysis of Epidemics on Networks', Journal of Systems Science and Complexity, 38, pp. 338 - 348, http://dx.doi.org/10.1007/s11424-025-4395-x

Rong X; Solo V, 2025, 'Asymptotic Classification Error for Heavy-Tailed Renewal Processes', IEEE Signal Processing Letters, 32, pp. 3769 - 3773, http://dx.doi.org/10.1109/LSP.2025.3611709

Rong X; Solo V, 2025, 'Asymptotic Error Rates for Point Process Classification', IEEE Transactions on Signal Processing, 73, pp. 738 - 750, http://dx.doi.org/10.1109/TSP.2025.3531373

Rong X; Solo V, 2025, 'Stable reduced-rank VAR identification', Automatica, 171, http://dx.doi.org/10.1016/j.automatica.2024.111961

Wang X; Solo V, 2025, 'Tangent Space Parametrization for Stochastic Differential Equations on SO(n)', IEEE Control Systems Letters, 9, pp. 1369 - 1374, http://dx.doi.org/10.1109/LCSYS.2025.3580034

Sundaram P; Luessi M; Bianciardi M; Stufflebeam S; Hamalainen M; Solo V, 2020, 'Individual Resting-State Brain Networks Enabled by Massive Multivariate Conditional Mutual Information', IEEE Transactions on Medical Imaging, 39, pp. 1957 - 1966, http://dx.doi.org/10.1109/TMI.2019.2962517

Godoy BI; Solo V; Pasha SA, 2020, 'Truncated Hawkes point process modeling: System theory and system identification', Automatica, 113, http://dx.doi.org/10.1016/j.automatica.2019.108733

Solo V; Greco MS; Mandic D; Djuric P; Spanias A; Bugallo MF, 2019, 'Innovation Starts with Education: ICASSP 2019 Education Panel [SP Forum]', IEEE Signal Processing Magazine, 36, pp. 135 - 147, http://dx.doi.org/10.1109/MSP.2019.2923280

Chung MK; Lee H; Di Christofano A; Ombao H; Solo V, 2019, 'Exact topological inference of the resting-state brain networks in twins', Network Neuroscience, 3, pp. 674 - 694, http://dx.doi.org/10.1162/netn_a_00091

Marjanovic G; Solo V, 2018, 'Numerical Methods for Stochastic Differential Equations in Matrix Lie Groups Made Simple', IEEE Transactions on Automatic Control, 63, pp. 4035 - 4050, http://dx.doi.org/10.1109/TAC.2018.2798703

Solo V; Poline JB; Lindquist MA; Simpson SL; Bowman FD; Chung MK; Cassidy B, 2018, 'Connectivity in fMRI: Blind Spots and Breakthroughs', IEEE Transactions on Medical Imaging, 37, pp. 1537 - 1550, http://dx.doi.org/10.1109/TMI.2018.2831261

Cassidy B; Bowman FD; Rae C; Solo V, 2018, 'On the Reliability of Individual Brain Activity Networks', IEEE Transactions on Medical Imaging, 37, pp. 649 - 662, http://dx.doi.org/10.1109/TMI.2017.2774364

Piggott MJ; Solo V, 2017, 'Correction to Diffusion LMS With Correlated Regressors I: Realization-wise Stability', IEEE Transactions on Signal Processing, http://dx.doi.org/10.1109/TSP.2017.2762280

Piggott MJ; Solo V, 2017, 'Diffusion LMS with Correlated Regressors II: Performance', IEEE Transactions on Signal Processing, 65, pp. 3934 - 3947, http://dx.doi.org/10.1109/TSP.2017.2703677

Piggott MJ; Solo V, 2016, 'Diffusion LMS with correlated Regressors I: Realization-wise stability', IEEE Transactions on Signal Processing, 64, pp. 5473 - 5484, http://dx.doi.org/10.1109/TSP.2016.2576426

Piggott MJ; Solo V, 2016, 'Geometric Euler-Maruyama schemes for stochastic differential equations in SO(n) and SE(n)?', SIAM Journal on Numerical Analysis, 54, pp. 2490 - 2516, http://dx.doi.org/10.1137/15M1019726

Solo V, 2016, 'State-space analysis of Granger-Geweke causality measures with application to fMRI', Neural Computation, 28, http://dx.doi.org/10.1162/NECO_a_00828

Cassidy B; Solo V, 2015, 'Spatially sparse, temporally smooth MEG via vector ℓ0', IEEE Transactions on Medical Imaging, 34, pp. 1282 - 1293, http://dx.doi.org/10.1109/TMI.2014.2383376

Cassidy B; Rae C; Solo V, 2015, 'Brain activity: Connectivity, sparsity, and mutual information', IEEE Transactions on Medical Imaging, 34, pp. 846 - 860, http://dx.doi.org/10.1109/TMI.2014.2358681

Ulfarsson MO; Solo V, 2015, 'Selecting the number of principal components with SURE', IEEE Signal Processing Letters, 22, pp. 239 - 243, http://dx.doi.org/10.1109/LSP.2014.2337276

Marjanovic G; Solo V, 2014, 'On lq optimization and sparse inverse covariance selection', IEEE Transactions on Signal Processing, 62, pp. 1644 - 1654, http://dx.doi.org/10.1109/TSP.2014.2303429

Marjanovic G; Solo V, 2014, 'Lq sparsity penalized linear regression with cyclic descent', IEEE Transactions on Signal Processing, 62, pp. 1464 - 1475, http://dx.doi.org/10.1109/TSP.2014.2302740

Seneviratne AJ; Solo V, 2014, 'Group sparsity via SURE based on regression parameter mean squared error', IEEE Signal Processing Letters, 21, pp. 1125 - 1129, http://dx.doi.org/10.1109/LSP.2014.2322085

Ulfarsson MO; Solo V, 2013, 'Tuning parameter selection for underdetermined reduced-rank regression', IEEE Signal Processing Letters, 20, pp. 881 - 884, http://dx.doi.org/10.1109/LSP.2013.2272463

Solo V; Pasha SA, 2013, 'Point-Process Principal Components Analysis via Geometric Optimization', Neural Computation, 25, pp. 101 - 122, http://dx.doi.org/10.1162/NECO_a_00382

Maher A; Solo V; Rae CD, 2013, 'Magnetic Resonance-based Metabolomics for Understanding Neurological Disorders: current status and statistical considerations.', Current Metabolomics, 1, pp. 2 - 14, http://dx.doi.org/10.2174/2213235X11301010002

Noh J; Solo V, 2013, 'Space-Time Separability in FMRI: Asymptotic Power Analysis and Cramér-Rao Lower Bounds', Signal Processing, IEEE Transactions on, 61, pp. 148 - 153, http://dx.doi.org/10.1109/TSP.2012.2226168

D. Maher A; Solo V; D. Rae C, 2012, 'Magnetic Resonance-Based Metabolomics for Understanding Neurological Disorders: Current Status and Statistical Considerations', Current Metabolomics, 1, pp. 2 - 14, http://dx.doi.org/10.2174/2213235x130102

Solo V; Pasha SA, 2012, 'A test for independence between a point process and an analogue signal', Journal of Time Series Analysis, 33, pp. 824 - 840, http://dx.doi.org/10.1111/j.1467-9892.2012.00790.x

Heaton C; Solo V, 2012, 'Estimation of high-dimensional linear factor models with grouped variables', Journal of Multivariate Analysis, 105, pp. 348 - 367, http://dx.doi.org/10.1016/j.jmva.2011.10.001

Cassidy B; Long C; Rae CD; Solo V, 2012, 'Identifying fMRI Model Violations with Lagrange Multiplier Tests', IEEE Transactions on Medical Imaging, 31, pp. 1481 - 1492, http://dx.doi.org/10.1109/TMI.2012.2195327

Goran M; Solo V, 2012, 'On lq Optimization and matrix completion', IEEE Transactions on Signal Processing, 60, pp. 5714 - 5724, http://dx.doi.org/10.1109/TSP.2012.2212015

Noh J; Solo V, 2011, 'Rician distributed FMRI: Asymptotic power analysis and cramér-rao lower bounds', IEEE Transactions on Signal Processing, 59, pp. 1322 - 1328, http://dx.doi.org/10.1109/TSP.2010.2098400

Ulfarsson MO; Solo V, 2011, 'Vector l0 sparse variable PCA', IEEE Transactions on Signal Processing, 59, pp. 1949 - 1958, http://dx.doi.org/10.1109/TSP.2011.2112653

Solo V; Freudenberg J; Middleton R, 2010, 'Stabilization and Disturbance Attenuation Over a Gaussian Communication Channel', IEEE Transactions on Automatic Control, 55, pp. 795 - 799

Lin F; Hara K; Solo V; Vangel M; Belliveau JW; Stufflebeam S; Hamalainen M, 2009, 'Dynamic Granger-Geweke causality modeling with application to interictal spike propagation', Human Brain Mapping, 30, pp. 1877 - 1886

Lin F-H; Hara K; Solo V; Vangel M; Belliveau J; Stufflebeam S; Hamalainen M, 2009, 'Dynamic Granger-Geweke causality modeling with application to interictal spike propagation', NeuroImage, 47, pp. S169 - S169, http://dx.doi.org/10.1016/s1053-8119(09)71812-9

Noh J; Solo V, 2008, 'Activation detection in functional MRI based on non-separable space-time noise models', 2008 5th IEEE International Symposium on Biomedical Imaging from Nano to Macro Proceedings Isbi, pp. 580 - 583, http://dx.doi.org/10.1109/ISBI.2008.4541062

Ulfarsson MO; Solo V, 2008, 'Dimension Estimation in Noisy PCA With SURE and Random Matrix Theory', IEEE Transactions on Signal Processing, 56, pp. 5804 - 5816

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