Recai Kılıç
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Co-authors
- İsmail ÖztürkMustafa AlçıFatma YıldırımUǧur ÇamMahmut TokmakçıHakan KuntmanÖmer Galip SaraçoğluAdem Kalınlı
- Topics
- Chaos control and synchronization (33 papers)Neural Networks and Applications (22 papers)stochastic dynamics and bifurcation (16 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Partner nations
- Türkiye
In The Last Decade
Recai Kılıç
58 papers receiving 594 citations
Peers
Comparison fields: 5 of 49
- Statistical and Nonlinear Physics 446
- Computer Networks and Communications 243
- Artificial Intelligence 158
- Computer Vision and Pattern Recognition 148
- Electrical and Electronic Engineering 132
Countries citing papers authored by Recai Kılıç
This map shows the geographic impact of Recai Kılıç'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 Recai Kılıç with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Recai Kılıç more than expected).
Fields of papers citing papers by Recai Kılıç
This network shows the impact of papers produced by Recai Kılıç. 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 Recai Kılıç. The network helps show where Recai Kılıç may publish in the future.
Co-authorship network of co-authors of Recai Kılıç
This figure shows the co-authorship network connecting the top 25 collaborators of Recai Kılıç. A scholar is included among the top collaborators of Recai Kılıç 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 Recai Kılıç. Recai Kılıç is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 7 | |
| 5 | 5 | |
| 6 | 14 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | Hardware verification: Determining the parameters of the modified Izhikevich neuron model with genetic algorithm | 1 |
| 10 | 33 | |
| 11 | 50 | |
| 12 | 1 | |
| 13 | Chaos training boards: versatile pedagogical tools for educating chaotic circuits and systems | 3 |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | A Realization of SC-CNN-Based Circuit Using FTFN | 4 |
| 19 | 21 | |
| 20 | 10 |
About Recai Kılıç
Recai Kılıç is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Cognitive Neuroscience, having authored 58 papers that have together received 632 indexed citations. Recurring topics across this work include Chaos control and synchronization (33 papers), Neural Networks and Applications (22 papers) and stochastic dynamics and bifurcation (16 papers). The work is most often cited by research in Statistical and Nonlinear Physics (446 citations), Computer Networks and Communications (243 citations) and Computer Vision and Pattern Recognition (148 citations). Recai Kılıç has collaborated with scholars based in Türkiye. Frequent co-authors include İsmail Öztürk, Mustafa Alçı, Fatma Yıldırım, Uǧur Çam, Mahmut Tokmakçı, Hakan Kuntman, Ömer Galip Saraçoğlu and Adem Kalınlı. Their work appears in journals such as Journal of the Franklin Institute, Electronics Letters and Chaos Solitons & Fractals.
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.