Alicia d’Anjou

1.0k total citations
48 papers, 749 citations indexed

About

Alicia d’Anjou is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computer Networks and Communications. According to data from OpenAlex, Alicia d’Anjou has authored 48 papers receiving a total of 749 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 17 papers in Statistical and Nonlinear Physics and 13 papers in Computer Networks and Communications. Recurrent topics in Alicia d’Anjou's work include Nonlinear Dynamics and Pattern Formation (12 papers), Neural dynamics and brain function (9 papers) and Neural Networks and Applications (9 papers). Alicia d’Anjou is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (12 papers), Neural dynamics and brain function (9 papers) and Neural Networks and Applications (9 papers). Alicia d’Anjou collaborates with scholars based in Spain, United Kingdom and France. Alicia d’Anjou's co-authors include Francisco Torrealdea, Manuel Graña, Abdelmalik Moujahid, C. Sarasola, F. Sanz, Carmen Hernández, Nieves Vélez de Mendizábal, Ramón Moreno, Raúl Orduna-Urrutia and José M. Asúa and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and Journal of Non-Crystalline Solids.

In The Last Decade

Alicia d’Anjou

47 papers receiving 704 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alicia d’Anjou Spain 15 400 320 260 128 125 48 749
Juan Hugo García-López Mexico 13 383 1.0× 87 0.3× 311 1.2× 25 0.2× 131 1.0× 55 572
Zhigang Zhu China 11 407 1.0× 392 1.2× 162 0.6× 135 1.1× 255 2.0× 31 639
Stavros G. Stavrinides Greece 12 275 0.7× 103 0.3× 146 0.6× 162 1.3× 325 2.6× 92 649
Minglin Ma China 18 711 1.8× 364 1.1× 314 1.2× 67 0.5× 526 4.2× 52 999
Yunzhen Zhang China 14 580 1.4× 340 1.1× 307 1.2× 42 0.3× 417 3.3× 35 800
Cong Xu China 16 304 0.8× 191 0.6× 382 1.5× 99 0.8× 639 5.1× 45 1.1k
Amalia Miliou Greece 22 147 0.4× 140 0.4× 159 0.6× 11 0.1× 1.2k 9.4× 122 1.6k
Zekun Deng China 10 307 0.8× 201 0.6× 154 0.6× 46 0.4× 295 2.4× 14 563
Dong Yu China 19 526 1.3× 517 1.6× 349 1.3× 152 1.2× 220 1.8× 39 1.1k
Bei Chen China 14 506 1.3× 304 0.9× 236 0.9× 49 0.4× 420 3.4× 34 777

Countries citing papers authored by Alicia d’Anjou

Since Specialization
Citations

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

Fields of papers citing papers by Alicia d’Anjou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alicia d’Anjou. 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 Alicia d’Anjou. The network helps show where Alicia d’Anjou may publish in the future.

Co-authorship network of co-authors of Alicia d’Anjou

This figure shows the co-authorship network connecting the top 25 collaborators of Alicia d’Anjou. A scholar is included among the top collaborators of Alicia d’Anjou 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 Alicia d’Anjou. Alicia d’Anjou 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.
Moujahid, Abdelmalik & Alicia d’Anjou. (2012). Metabolic efficiency with fast spiking in the squid axon. Frontiers in Computational Neuroscience. 6. 95–95. 13 indexed citations
2.
Moujahid, Abdelmalik, Alicia d’Anjou, Francisco Torrealdea, & Francisco Torrealdea. (2011). Efficient synchronization of structurally adaptive coupled Hindmarsh–Rose neurons. Chaos Solitons & Fractals. 44(11). 929–933. 36 indexed citations
3.
Moreno, Ramón, et al.. (2010). Linked multi-component mobile robots: Modeling, simulation and control. Robotics and Autonomous Systems. 58(12). 1292–1305. 25 indexed citations
4.
Torrealdea, Francisco, C. Sarasola, Alicia d’Anjou, Abdelmalik Moujahid, & Nieves Vélez de Mendizábal. (2009). Energy efficiency of information transmission by electrically coupled neurons. Biosystems. 97(1). 60–71. 43 indexed citations
5.
Hernández, Carmen, et al.. (2008). On the ability of Swarms to compute the 3-coloring of graphs. Artificial Life. 102–109. 7 indexed citations
6.
García‐Sebastián, Maite, Carmen Hernández, & Alicia d’Anjou. (2008). Robustness of an adaptive MRI segmentation algorithm parametric intensity inhomogeneity modeling. Neurocomputing. 72(10-12). 2146–2152. 3 indexed citations
7.
Duro, Richard J., et al.. (2005). Information Processing With Evolutionary Algorithms: From Industrial Applications To Academic Speculations (Advanced Information and Knowledge Processing). Springer eBooks.
8.
Graña, Manuel, et al.. (2005). Morphological memories for feature extraction in hyperspectral images.. The European Symposium on Artificial Neural Networks. 497–502. 3 indexed citations
9.
Sarasola, C., Alicia d’Anjou, Francisco Torrealdea, & Manuel Graña. (2005). Minimization of the energy flow in the synchronization of nonidentical chaotic systems. Physical Review E. 72(2). 26223–26223. 8 indexed citations
10.
Sarasola, C., Francisco Torrealdea, Alicia d’Anjou, Abdelmalik Moujahid, & Manuel Graña. (2004). Energy balance in feedback synchronization of chaotic systems. Physical Review E. 69(1). 11606–11606. 107 indexed citations
11.
d’Anjou, Alicia, Francisco Torrealdea, José R. Leiza, José M. Asúa, & Gurutze Arzamendi. (2003). Model Reduction in Emulsion Polymerization Using Hybrid First‐Principles/Artificial Neural Network Models. Macromolecular Theory and Simulations. 12(1). 42–56. 13 indexed citations
12.
d’Anjou, Alicia, C. Sarasola, Francisco Torrealdea, & Manuel Graña. (2002). Parameter adaptive global synchronization of Lorenz chaotic systems. 471–476. 2 indexed citations
13.
Graña, Manuel, et al.. (2001). Experimental results of an evolution-based adaptation strategy for VQ image filtering. Information Sciences. 133(3-4). 249–266. 10 indexed citations
14.
Graña, Manuel, et al.. (2000). A near real-time Evolution-based Adaptation Strategy for dynamic Color Quantization of image sequences. Information Sciences. 122(2-4). 161–183. 3 indexed citations
15.
Graña, Manuel, et al.. (1997). Self organizing map for adaptive non-stationary clustering: some experimental results on color quantization of image sequences.. The European Symposium on Artificial Neural Networks. 1 indexed citations
16.
d’Anjou, Alicia, et al.. (1997). Structure of the high-order Boltzmann machine from independence maps. IEEE Transactions on Neural Networks. 8(6). 1351–1358. 2 indexed citations
17.
d’Anjou, Alicia, et al.. (1996). Convergence Properties of High-order Boltzmann Machines. Neural Networks. 9(9). 1561–1567. 3 indexed citations
18.
d’Anjou, Alicia, et al.. (1995). The high-order Boltzmann machine: learned distribution and topology. IEEE Transactions on Neural Networks. 6(3). 767–770. 11 indexed citations
19.
Graña, Manuel, et al.. (1994). High-order Boltzmann machines applied to the Monk's problems.. The European Symposium on Artificial Neural Networks. 1 indexed citations
20.
d’Anjou, Alicia, et al.. (1991). Máquinas de Boltzmann para la resolución del problema de la satisfacibilidad. 24(1). 40–49. 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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