Will Gersch

3.0k total citations
56 papers, 2.0k citations indexed

About

Will Gersch is a scholar working on Control and Systems Engineering, Signal Processing and Civil and Structural Engineering. According to data from OpenAlex, Will Gersch has authored 56 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Control and Systems Engineering, 13 papers in Signal Processing and 12 papers in Civil and Structural Engineering. Recurrent topics in Will Gersch's work include Structural Health Monitoring Techniques (12 papers), Fault Detection and Control Systems (10 papers) and EEG and Brain-Computer Interfaces (8 papers). Will Gersch is often cited by papers focused on Structural Health Monitoring Techniques (12 papers), Fault Detection and Control Systems (10 papers) and EEG and Brain-Computer Interfaces (8 papers). Will Gersch collaborates with scholars based in United States, Japan and Canada. Will Gersch's co-authors include Genshiro Kitagawa, G. Kitagawa, Graham V. Goddard, Daniel Sharpe, Eugene Dong, Hirotugu Akaike, N. Norby Nielsen, Douglas A. Foutch, Sushan Luo and T. Brotherton and has published in prestigious journals such as Science, Journal of the American Statistical Association and IEEE Transactions on Automatic Control.

In The Last Decade

Will Gersch

53 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Will Gersch United States 23 454 424 386 384 321 56 2.0k
Manfred Deistler Austria 23 333 0.7× 1.2k 2.8× 265 0.7× 252 0.7× 183 0.6× 116 2.6k
Charlotte Striebel United States 8 739 1.6× 456 1.1× 109 0.3× 128 0.3× 62 0.2× 15 1.7k
Tohru Ozaki Japan 29 516 1.1× 607 1.4× 37 0.1× 322 0.8× 873 2.7× 114 2.9k
P.M.T. Broersen Netherlands 23 374 0.8× 601 1.4× 226 0.6× 460 1.2× 83 0.3× 123 1.8k
Herbert E. Rauch United States 14 887 2.0× 637 1.5× 133 0.3× 169 0.4× 69 0.2× 43 2.0k
Hua‐Liang Wei United Kingdom 37 959 2.1× 1.5k 3.6× 304 0.8× 409 1.1× 530 1.7× 161 4.1k
Joaquı́n Mı́guez Spain 21 1.4k 3.0× 417 1.0× 176 0.5× 385 1.0× 39 0.1× 132 2.6k
Filip Mulier United States 8 906 2.0× 279 0.7× 92 0.2× 190 0.5× 94 0.3× 10 1.9k
Ursula Gather Germany 22 347 0.8× 162 0.4× 52 0.1× 160 0.4× 49 0.2× 93 2.0k
Marvin H. J. Gruber United States 8 293 0.6× 276 0.7× 167 0.4× 575 1.5× 189 0.6× 15 2.1k

Countries citing papers authored by Will Gersch

Since Specialization
Citations

This map shows the geographic impact of Will Gersch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Will Gersch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Gersch more than expected).

Fields of papers citing papers by Will Gersch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Will Gersch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Will Gersch. The network helps show where Will Gersch may publish in the future.

Co-authorship network of co-authors of Will Gersch

This figure shows the co-authorship network connecting the top 25 collaborators of Will Gersch. A scholar is included among the top collaborators of Will Gersch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Will Gersch. Will Gersch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gersch, Will & G. Kitagawa. (2002). Smoothness priors analysis of quasi-periodic time series. 2. 1091–1095. 4 indexed citations
2.
Gersch, Will, et al.. (1995). Multivariate autoregressive time semes modeling: one scalar autoregressive model at-A-time. Communication in Statistics- Theory and Methods. 24(11). 2715–2733. 2 indexed citations
3.
Gersch, Will, et al.. (1990). Multichannel time varying autoregressive modeling: a circular lattice-smoothness priors realization. assp 32. 859–860 vol.2. 1 indexed citations
4.
Kitagawa, Genshiro & Will Gersch. (1984). A Smoothness Priors–State Space Modeling of Time Series with Trend and Seasonality. Journal of the American Statistical Association. 79(386). 378–389. 173 indexed citations
5.
Gersch, Will & Genshiro Kitagawa. (1983). The Prediction of Time Series With Trends and Seasonalities. Journal of Business and Economic Statistics. 1(3). 253–264. 77 indexed citations
6.
Gersch, Will & T. Brotherton. (1982). Estimation of stationary structural system parameters from non-stationary random vibration data: A locally stationary model method. Journal of Sound and Vibration. 81(2). 215–227. 16 indexed citations
7.
Gersch, Will, T. Brotherton, & Simone Braun. (1980). Parametric time domain analysis of the multiple input/scalar output problem: The source identification problem. Journal of Sound and Vibration. 69(3). 441–460. 3 indexed citations
8.
Gersch, Will, et al.. (1977). Automatic classification of EEGs: A parametric model new features for classification approach. IEEE Transactions on Automatic Control. 14(14). 762–769. 5 indexed citations
9.
Gersch, Will, et al.. (1977). Automatic classification of multivariate EEGs using an amount of information measure and the eigenvalues of parametric time series model features. Computers and Biomedical Research. 10(3). 297–318. 30 indexed citations
10.
Gersch, Will, et al.. (1977). Parametric time series models for multivariate EEG analysis. Computers and Biomedical Research. 10(2). 113–125. 55 indexed citations
11.
Gersch, Will, et al.. (1976). Structural System Parameter Estimation by Two-Stage Least Squares Method. Journal of the Engineering Mechanics Division. 102(5). 883–899. 15 indexed citations
12.
Gersch, Will, et al.. (1975). PVC detection by the heart-beat interval data—Markov chain approach. Computers and Biomedical Research. 8(4). 370–378. 14 indexed citations
13.
Tharp, Barry R. & Will Gersch. (1975). Spectral analysis of seizures in humans. Computers and Biomedical Research. 8(6). 503–521. 16 indexed citations
14.
Gersch, Will & Douglas A. Foutch. (1974). Least squares estimates of structural system parameters using covariance function data. IEEE Transactions on Automatic Control. 19(6). 898–903. 34 indexed citations
15.
Gersch, Will & Daniel Sharpe. (1973). Estimation of power spectra with finite-order autoregressive models. IEEE Transactions on Automatic Control. 18(4). 367–369. 61 indexed citations
16.
Gersch, Will. (1972). Causality or driving in electrophysiological signal analysis. Mathematical Biosciences. 14(1-2). 177–196. 39 indexed citations
17.
Gersch, Will & Sushan Luo. (1972). Discrete Time Series Synthesis of Randomly Excited Structural System Response. The Journal of the Acoustical Society of America. 51(1B). 402–408. 26 indexed citations
18.
Gersch, Will. (1969). Average Power and Power Exchange in Oscillators. The Journal of the Acoustical Society of America. 46(5B). 1180–1185. 7 indexed citations
19.
Gersch, Will. (1961). The Effects of Time Weighting the Input to a Spectrum Analyzer. IRE Transactions on Circuit Theory. 8(2). 121–126. 3 indexed citations
20.
Gersch, Will, et al.. (1960). Spectral Measurements of Sliding Tones. IRE Transactions on Circuit Theory. 7(5). 26–39. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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