Johan Sandberg, Ph.D.

Johan Sandberg was born in 1980 in Sweden. He received the M.Sc. degree in Engineering Physics in 2005 and the Ph.D. degree in Mathematical Statistics in 2010, both at the Centre for Mathematical Sciences at Lund University, Sweden. The main contributions of his Ph.D. thesis are a few theorems that form a framework for time-frequency analysis of non-stationary time series in discrete time rather than in continuous time. Apart from time-frequency analysis, his research field has included spectrum and cepstrum estimation of audio signals.

Since 2010, Johan Sandberg has worked within finance and risk analysis. Today, he leads the counterparty credit risk modelling team in Nordea.

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Publications

Journal Papers

• M. Hansson-Sandsten and J. Sandberg, “Mean Square Error Optimal Multiple Windows for Cepstrum Estimation,” in revision.
• T. Kinnunen, R. Saeidi, F. Sedlák, K-A Lee, J. Sandberg, M. Hansson-Sandsten, H. Li, “Low-Variance Multitaper MFCC Features: a Case Study in Robust Speaker Verification,” accepted for publication in IEEE Transactions on Audio, Speech and Language Processing, 2012.
• J. Sandberg and M. Hansson-Sandsten, “Optimal Cepstrum Smoothing,” Signal Processing, vol. 92, no. 5, pp. 1290-1301, doi: 10.1016/j.sigpro.2011.11.026, 2012.
   Find at Science Direct
• J. Sandberg and M. Hansson-Sandsten, “Optimal Non-Parametric Covariance Function Estimation for any Family of Non-Stationary Random Processes,” EURASIP Journal on Advances in Signal Processing, vol. 2011, Article ID 140797, doi:10.1155/2011/140797, 2011.
   Find at Journal Homepage
• J. Sandberg, M. Hansson-Sandsten, T. Kinnunen, R. Saeidi, P. Flandrin, and P. Borgnat, “Multitaper Estimation of Frequency-Warped Cepstra with Application to Speaker Verification,” IEEE Signal Processing Letters, vol. 17, no. 4, pp. 343-346, doi: 10.1109/LSP.2010.2040228, 2010.
   Find at IEEE Explore
• J. Sandberg and M. Hansson-Sandsten, “Optimal Stochastic Discrete Time-Frequency Analysis in the Ambiguity and Time-Lag Domain,” Signal Processing, vol. 90, no. 7, pp. 2203-2211, doi: 10.1016/j.sigpro.2010.01.028, 2010.
   Find at Science Direct
• M. Hansson-Sandsten and J. Sandberg, “Optimization of Weighting Factors for Multiple Window Spectrogram of Event Related Potentials,” EURASIP Journal on Advances in Signal Processing vol. 2010, doi: 10.1155/2010/391798, 2010.
   Find at Journal Homepage
• J. Sandberg and M. Hansson-Sandsten, “A Comparison Between Different Discrete Ambiguity Domain Definitions in Stochastic Time-Frequency Analysis,” IEEE Transactions on Signal Processing, vol. 57, no. 3, pp. 868-877, doi: 10.1109/TSP.2008.2009892, 2009.
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Conference Proceedings

• C. Hanilci, T. Kinnunen, R. Saeidi, J. Pohjalainen, P. Alku, F. Ertas, J. Sandberg, and M. Hansson-Sandsten, “Comparing Spectrum Estimators in Speaker Verification Under Additive Noise Degradation,” accepted for publication in Proceedings of the ICASSP, IEEE International Conference on Acoustics, Speech, and Signal Processing, Kyoto, Japan. March 2012.
• T. Kinnunen, R. Saeidi, J. Sandberg, and M. Hansson-Sandsten, “What Else is New Than the Hamming Window? Robust MFCCs for Speaker Recognition via Multitapering,” Interspeech, 2010, Makuhari, Japan. September 2010, pp. 2734-2737.
   Find at Interspeech Archive
• J. Sandberg and M. Hansson-Sandsten, “Approximate Optimal Periodogram Smoothing for Cepstrum Estimation using a Penalty Term,” Proceedings of the EUSIPCO, European Signal Processing Conference 2010, Aalborg, Denmark. August 2010, pp. 363-367.
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• J. Sandberg and M. Sandsten, “Optimal Wigner Cross-Spectrum estimation,” in Proceedings of the EUSIPCO, European Signal Processing Conference 2009, Glasgow, UK. August 2009, pp. 2298-2302.
• M. Sandsten and J. Sandberg, “Optimization of Weighting Factors for Multiple Window Time-Frequency Analysis,” in Proceedings of the EUSIPCO, European Signal Processing Conference 2009, Glasgow, UK. August 2009, pp. 2283-2287.
• M. Sandsten and J. Sandberg, “Optimal Cepstrum Estimation Using Multiple Windows,” Proceedings of the ICASSP, IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan. April 2009, pp. 3077-3080, doi: 10.1109/ICASSP.2009.4960274.
   Find at IEEE Explore
• J. Sandberg and M. Hansson, “Coherence Estimation between EEG Signals using Multiple Window Time-Frequency Analysis compared to Gaussian Kernels,” Proceedings of the EUSIPCO, European Signal Processing Conference, Florence, Italy. Sept. 2006.
• J. Sandberg, M. Hansson, and M. Lindgren, “Detecting MMN in Infants EEG with Singular Value Decomposition,” Proceedings of the EMBC, 27th Annual Int. Conf of the IEEE Engineering in Medicine and Biology Society, Shanghai, China. Sept. 2005, pp. 4227-4230, doi: 10.1109/IEMBS.2005.1615397.
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• M. Hansson and J. Sandberg, “Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram,” Proceedings of the EMBC, 27th Annual Int. Conf of the IEEE Engineering in Medicine and Biology Society, Shanghai, China. Sept. 2005, pp. 7293-7296, doi: 10.1109/IEMBS.2005.1616195.
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Theses

• J. Sandberg, “Discrete Stochastic Time-Frequency Analysis and Cepstrum Estimation,” Doctoral Thesis in Mathematical Statistics, 2010. ISBN: 978-91-628-8080-4. Advisor: Professor Maria Hansson-Sandsten, Opponent: Professor Magnus Jansson, Royal Institute of Technology, Stockholm.
   Find at Libris (National Library of Sweden)
• J. Sandberg, “Ambiguity Domain Definitions and Covariance Function Estimation for Non-Stationary Random Processes in Discrete Time,” Licentiate Thesis in Mathematical Statistics, 2008. Advisor: Professor Maria Hansson-Sandsten, Opponent: Professor Martin Stridh.
• J. Sandberg, “Detecting MMN in Infants EEG with Bootstrap and SVD,” Master Thesis in Mathematical Statistics, 2005.