D.A. Miller

444 total citations
31 papers, 345 citations indexed

About

D.A. Miller is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, D.A. Miller has authored 31 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistical and Nonlinear Physics, 13 papers in Computer Networks and Communications and 11 papers in Artificial Intelligence. Recurrent topics in D.A. Miller's work include Chaos control and synchronization (14 papers), Nonlinear Dynamics and Pattern Formation (13 papers) and Neural Networks and Applications (11 papers). D.A. Miller is often cited by papers focused on Chaos control and synchronization (14 papers), Nonlinear Dynamics and Pattern Formation (13 papers) and Neural Networks and Applications (11 papers). D.A. Miller collaborates with scholars based in United States, Italy and France. D.A. Miller's co-authors include Giuseppe Grassi, A. Lozowski, Jacek M. Żurada, John‐Mary Vianney, John M. Spitsbergen, Bradley J. Bazuin, Nicholas Anderson, Michael J. Bamshad, Julia M. Crouch and Seema M. Jamal and has published in prestigious journals such as Brain Research, SAE technical papers on CD-ROM/SAE technical paper series and Chaos Solitons & Fractals.

In The Last Decade

D.A. Miller

27 papers receiving 322 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D.A. Miller United States 11 255 160 95 34 33 31 345
Santo Banerjee Malaysia 12 301 1.2× 189 1.2× 112 1.2× 19 0.6× 45 1.4× 23 368
Banlue Srisuchinwong Thailand 11 357 1.4× 240 1.5× 77 0.8× 18 0.5× 55 1.7× 51 436
Sishu Shankar Muni India 14 382 1.5× 251 1.6× 61 0.6× 27 0.8× 40 1.2× 49 502
Juan Gonzalo Barajas-Ramírez Mexico 9 229 0.9× 204 1.3× 41 0.4× 10 0.3× 16 0.5× 34 325
Chunde Yang China 11 102 0.4× 177 1.1× 20 0.2× 7 0.2× 40 1.2× 26 345
Xiangliang Xu China 11 200 0.8× 70 0.4× 155 1.6× 28 0.8× 18 0.5× 21 319
Gualberto Solı́s-Perales Mexico 9 380 1.5× 365 2.3× 41 0.4× 9 0.3× 33 1.0× 29 465
Shaohui Yan China 14 327 1.3× 141 0.9× 208 2.2× 24 0.7× 44 1.3× 49 453
Tianai Lu China 9 332 1.3× 182 1.1× 83 0.9× 14 0.4× 41 1.2× 10 377
Xiaofeng Gong China 11 248 1.0× 258 1.6× 31 0.3× 5 0.1× 26 0.8× 26 373

Countries citing papers authored by D.A. Miller

Since Specialization
Citations

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

Fields of papers citing papers by D.A. Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.A. Miller. 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 D.A. Miller. The network helps show where D.A. Miller may publish in the future.

Co-authorship network of co-authors of D.A. Miller

This figure shows the co-authorship network connecting the top 25 collaborators of D.A. Miller. A scholar is included among the top collaborators of D.A. Miller 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 D.A. Miller. D.A. Miller 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.
Miller, D.A., et al.. (2023). Autonomous Eco-Driving Evaluation of an Electric Vehicle on a Chassis Dynamometer. SAE technical papers on CD-ROM/SAE technical paper series. 1. 2 indexed citations
2.
Miller, D.A., et al.. (2020). Benefits Of A Hands On Introduction To Electrical And Computer Engineering. Papers on Engineering Education Repository (American Society for Engineering Education). 8.264.1–8.264.10. 1 indexed citations
3.
Tabor, Holly K., Seema M. Jamal, Joon‐Ho Yu, et al.. (2016). My46: a Web-based tool for self-guided management of genomic test results in research and clinical settings. Genetics in Medicine. 19(4). 467–475. 25 indexed citations
4.
Vianney, John‐Mary, D.A. Miller, & John M. Spitsbergen. (2014). Effects of acetylcholine and electrical stimulation on glial cell line-derived neurotrophic factor production in skeletal muscle cells. Brain Research. 1588. 47–54. 13 indexed citations
5.
Grassi, Giuseppe, et al.. (2012). A new scheme to synchronize chaotic discrete-time systems via a scalar signal. 34. 654–657. 2 indexed citations
6.
Miller, D.A., et al.. (2011). Exploring optimal current stimuli that provide membrane voltage tracking in a neuron model. Biological Cybernetics. 104(3). 185–195. 6 indexed citations
7.
Grassi, Giuseppe & D.A. Miller. (2011). Dead-beat full state hybrid projective synchronization for chaotic maps using a scalar synchronizing signal. Communications in Nonlinear Science and Numerical Simulation. 17(4). 1824–1830. 10 indexed citations
8.
Grassi, Giuseppe & D.A. Miller. (2011). Synchronizing chaotic systems up to an arbitrary scaling matrix via a single signal. Applied Mathematics and Computation. 218(10). 6118–6124. 6 indexed citations
9.
Miller, D.A.. (2009). Where is the Why if the What is in How? The Issue of Intent in “Unintentional Ideal Communities”. Journal for Cultural Research. 13(1). 29–52. 1 indexed citations
10.
Grassi, Giuseppe, et al.. (2008). Multi-wing hyperchaotic attractors from coupled Lorenz systems. Chaos Solitons & Fractals. 41(1). 284–291. 53 indexed citations
11.
Grassi, Giuseppe, et al.. (2008). GENERATION OF A FOUR-WING CHAOTIC ATTRACTOR BY TWO WEAKLY-COUPLED LORENZ SYSTEMS. International Journal of Bifurcation and Chaos. 18(7). 2089–2094. 19 indexed citations
12.
Grassi, Giuseppe & D.A. Miller. (2007). Arbitrary observer scaling of all chaotic drive system states via a scalar synchronizing signal. Chaos Solitons & Fractals. 39(3). 1246–1252. 10 indexed citations
13.
Grassi, Giuseppe & D.A. Miller. (2007). PROJECTIVE SYNCHRONIZATION VIA A LINEAR OBSERVER: APPLICATION TO TIME-DELAY, CONTINUOUS-TIME AND DISCRETE-TIME SYSTEMS. International Journal of Bifurcation and Chaos. 17(4). 1337–1342. 22 indexed citations
14.
Miller, D.A., et al.. (2003). Experimental performance of a coherent communication system based on hyperchaos synchronization. 3. III–516. 1 indexed citations
15.
Miller, D.A., et al.. (2003). A hybrid analog/digital circuit for experiments in controlling chaos. 1. I–188. 1 indexed citations
16.
Drăghici, Sorin & D.A. Miller. (2003). A VLSI neural network classifier based on integer-valued weights. 4. 2419–2424.
17.
Barr, Justinn & D.A. Miller. (2002). A hybrid analog/digital chaotic associative memory. 3. 1018–1021. 2 indexed citations
18.
Miller, D.A. & Giuseppe Grassi. (2002). A discrete generalized hyperchaotic Henon map circuit. 1. 328–331. 21 indexed citations
19.
Miller, D.A. & Giuseppe Grassi. (2001). Experimental realization of observer-based hyperchaos synchronization. IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications. 48(3). 366–374. 47 indexed citations
20.
Miller, D.A. & Jacek M. Żurada. (1998). A dynamical system perspective of structural learning with forgetting. IEEE Transactions on Neural Networks. 9(3). 508–515. 9 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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