Summary
Andrew Walden's primary research interest is best described as statistical signal processing, covering time series, spectral analysis and wavelets. #
He is particularly interested in making these areas as accessible as possible through careful attention to practical implementation issues. His books, co-authored with Don Percival, on Spectral Analysis and on Wavelets attempt to achieve this goal. #
He is particularly interested in statistical signal processing for the physical sciences and medicine, and spent nine years as a researcher with BP before coming to Imperial College.
RECENT Invited Lectures and Presentations
- Invited organizer for, and speaker at, session "Time Series" at the 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, December 2017
Publications
Journals
Lutzeyer JF, Walden AT, 2020, Comparing Spectra of Graph Shift Operator Matrices, ISSN:1860-949X, Pages:191-202
Walden A, Zhuang L, 2019, Constructing brain connectivity group graphs from EEG time series, Journal of Applied Statistics, Vol:46, ISSN:0266-4763, Pages:1107-1128
Walden AT, Leong ZZ, 2018, Tapering promotes propriety for Fourier transforms of real-valued time series, Ieee Transactions on Signal Processing, Vol:66, ISSN:1053-587X, Pages:4585-4597
Books
Percival D, Walden A, 2020, Spectral Analysis for Univariate Time Series, Cambridge University Press, ISBN:9781139235723
Conference
Lutzeyer J, Walden A, Comparing Spectra of Graph Shift Operator Matrices, COMPLEX NETWORKS 2019: The 8th International Conference on Complex Networks and Their Applications VIII, Springer Verlag, ISSN:1860-949X