Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Variable structure control of nonlinear multivariable systems: a tutorial
19881.4k citationsStanisław H. Żak et al.profile →
Countries citing papers authored by Stanisław H. Żak
Since
Specialization
Citations
This map shows the geographic impact of Stanisław H. Żak'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 Stanisław H. Żak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stanisław H. Żak more than expected).
Fields of papers citing papers by Stanisław H. Żak
This network shows the impact of papers produced by Stanisław H. Żak. 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 Stanisław H. Żak. The network helps show where Stanisław H. Żak may publish in the future.
Co-authorship network of co-authors of Stanisław H. Żak
This figure shows the co-authorship network connecting the top 25 collaborators of Stanisław H. Żak.
A scholar is included among the top collaborators of Stanisław H. Żak 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 Stanisław H. Żak. Stanisław H. Żak is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yuan, Liangqi, et al.. (2023). Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges. IEEE Transactions on Intelligent Vehicles. 9(1). 119–137.89 indexed citations breakdown →
Hui, S. & Stanisław H. Żak. (2019). Discrete Fourier transform and permutations. Bulletin of the Polish Academy of Sciences Technical Sciences. 995–1005.3 indexed citations
Chakrabarty, Ankush, Gregery T. Buzzard, Stanisław H. Żak, Fanglai Zhu, & Ann E. Rundell. (2015). Simultaneous Unknown Input And Sensor Noise Reconstruction For Nonlinear Systems With Boundary Layer Sliding Mode Observers.. arXiv (Cornell University).3 indexed citations
12.
Hui, S., et al.. (2014). SLIDING MODE WHEEL SLIP CONTROLLER FOR AN ANTILOCK BRAKING SYSTEM. International Journal of Vehicle Design. 19(4). 523–539.8 indexed citations
13.
Chong, Edwin K. P. & Stanisław H. Żak. (2013). An Introduction to Optimization Ed. 4. John Wiley & Sons eBooks.1 indexed citations
14.
Hui, Stefen & Stanisław H. Żak. (2005). Observer design for systems with unknown inputs. International Journal of Applied Mathematics and Computer Science. 15(4). 431–446.169 indexed citations
15.
Żak, Stanisław H., et al.. (2005). IMAGE RECALL USING A LARGE SCALE GENERALIZED BRAIN-STATE-IN-A-BOX NEURAL NETWORK. International Journal of Applied Mathematics and Computer Science. 15(1). 99–114.7 indexed citations
16.
Żak, Stanisław H., et al.. (2002). Llarge scale neural associative memory design. PRZEGLĄD ELEKTROTECHNICZNY. 78(10). 220–224.3 indexed citations
17.
Żak, Stanisław H., et al.. (1999). CHAOTIC NEURAL FUZZY ASSOCIATIVE MEMORY. International Journal of Bifurcation and Chaos. 9(8). 1597–1617.3 indexed citations
18.
Hui, Stefen, et al.. (1993). Dynamics and stability analysis of the Brain-State-in-a-Box (BSB) neural models. Oxford University Press eBooks. 212–224.2 indexed citations
19.
Walcott, B.L. & Stanisław H. Żak. (1987). Combined Observer-Controller Synthesis for Nonlinear/Uncertain Dynamical Systems. American Control Conference. 868–873.2 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.