R.S. Schneider

772 total citations
11 papers, 618 citations indexed

About

R.S. Schneider is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, R.S. Schneider has authored 11 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 5 papers in Artificial Intelligence and 2 papers in Control and Systems Engineering. Recurrent topics in R.S. Schneider's work include Neural Networks and Applications (4 papers), Advanced Memory and Neural Computing (3 papers) and Power Quality and Harmonics (3 papers). R.S. Schneider is often cited by papers focused on Neural Networks and Applications (4 papers), Advanced Memory and Neural Computing (3 papers) and Power Quality and Harmonics (3 papers). R.S. Schneider collaborates with scholars based in Canada and United States. R.S. Schneider's co-authors include Deepak Divan, W.E. Brumsickle, M. McGranaghan, G.A. Luckjiff, I. S. Grant, R.W. Gascoigne, Dale T. Bradshaw, Michael Ingram, Bertolt Kranz and A. Bendre and has published in prestigious journals such as IEEE Transactions on Industry Applications, IEEE Transactions on Power Delivery and International Journal of Neural Systems.

In The Last Decade

R.S. Schneider

10 papers receiving 568 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
R.S. Schneider Canada	6	604	329	127	35	31	11	618
C. Fitzer United Kingdom	11	828 1.4×	402 1.2×	256 2.0×	37 1.1×	44 1.4×	16	852
Byung-Yeol Bae South Korea	10	617 1.0×	332 1.0×	186 1.5×	20 0.6×	65 2.1×	15	637
Amit Kumar Jindal India	8	527 0.9×	284 0.9×	153 1.2×	14 0.4×	13 0.4×	16	550
C.J. Melhorn United States	10	345 0.6×	159 0.5×	57 0.4×	36 1.0×	14 0.5×	17	366
Luís F. C. Monteiro Brazil	13	468 0.8×	225 0.7×	141 1.1×	9 0.3×	35 1.1×	55	491
C. González Spain	12	522 0.9×	378 1.1×	48 0.4×	7 0.2×	43 1.4×	39	550
Daniel Bejmert Poland	10	302 0.5×	227 0.7×	35 0.3×	17 0.5×	19 0.6×	25	341
Dayi Li China	8	311 0.5×	206 0.6×	72 0.6×	9 0.3×	22 0.7×	45	333
Daniel J. Carnovale United States	9	274 0.5×	128 0.4×	45 0.4×	17 0.5×	23 0.7×	17	308
Gabrio Superti-Furga Italy	12	582 1.0×	278 0.8×	181 1.4×	5 0.1×	15 0.5×	50	605

Countries citing papers authored by R.S. Schneider

Since Specialization

Citations

This map shows the geographic impact of R.S. Schneider'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 R.S. Schneider with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R.S. Schneider more than expected).

Fields of papers citing papers by R.S. Schneider

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R.S. Schneider. 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 R.S. Schneider. The network helps show where R.S. Schneider may publish in the future.

Co-authorship network of co-authors of R.S. Schneider

This figure shows the co-authorship network connecting the top 25 collaborators of R.S. Schneider. A scholar is included among the top collaborators of R.S. Schneider 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 R.S. Schneider. R.S. Schneider is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Divan, Deepak, W.E. Brumsickle, R.S. Schneider, et al.. (2007). A Distributed Static Series Compensator System for Realizing Active Power Flow Control on Existing Power Lines. IEEE Transactions on Power Delivery. 22(1). 642–649. 171 indexed citations

2.

Divan, Deepak, W.E. Brumsickle, R.S. Schneider, et al.. (2005). A distributed static series compensator system for realizing active power flow control on existing power lines. 357–364. 60 indexed citations

3.

Divan, Deepak, et al.. (2004). Dual source dynamic sag correctors-a cost effective topology for enhancing the reliability of dual source systems. 2. 940–947. 10 indexed citations

4.

Bendre, A., et al.. (2004). Application of zig-zag transformers in a three-wire three-phase dynamic sag corrector system. 3. 1260–1265. 9 indexed citations

5.

Brumsickle, W.E., G.A. Luckjiff, R.S. Schneider, Deepak Divan, & M. McGranaghan. (2003). Dynamic sag correctors: cost effective industrial power line conditioning. 2. 1339–1344. 162 indexed citations

6.

Card, H.C., et al.. (2002). The impact of VLSI fabrication on neural learning. 2. 985–988. 1 indexed citations

7.

Card, H.C., et al.. (2002). Is VLSI neural learning robust against circuit limitations?. 3. 1889–1893.

8.

Brumsickle, W.E., R.S. Schneider, G.A. Luckjiff, Deepak Divan, & M. McGranaghan. (2001). Dynamic sag correctors: cost-effective industrial power line conditioning. IEEE Transactions on Industry Applications. 37(1). 212–217. 197 indexed citations

9.

Schneider, R.S.. (2000). Instabilities and Oscillation in the Deterministic Boltzmann Machine. International Journal of Neural Systems. 10(4). 321–330. 1 indexed citations

10.

Schneider, R.S. & H.C. Card. (1998). Analog hardware implementation issues in deterministic Boltzmann machines. IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing. 45(3). 352–360. 4 indexed citations

11.

Card, H.C., et al.. (1994). Learning capacitive weights in analog CMOS neural networks. The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology. 8(3). 209–225. 3 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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