P. Pajunen

1.1k total citations
17 papers, 581 citations indexed

About

P. Pajunen is a scholar working on Signal Processing, Artificial Intelligence and Analytical Chemistry. According to data from OpenAlex, P. Pajunen has authored 17 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Signal Processing, 7 papers in Artificial Intelligence and 6 papers in Analytical Chemistry. Recurrent topics in P. Pajunen's work include Blind Source Separation Techniques (15 papers), Speech and Audio Processing (9 papers) and Neural Networks and Applications (7 papers). P. Pajunen is often cited by papers focused on Blind Source Separation Techniques (15 papers), Speech and Audio Processing (9 papers) and Neural Networks and Applications (7 papers). P. Pajunen collaborates with scholars based in Finland, United Kingdom and Japan. P. Pajunen's co-authors include Aapo Hyvärinen, Juha Karhunen, Erkki Oja, Andrzej Cichocki, Włodzimierz Kasprzak, Hanna Kortejärvi, Arto Urtti, Mark D. Plumbley, Marjo Yliperttula and Martti Marvola and has published in prestigious journals such as Journal of Pharmaceutical Sciences, Neurocomputing and Neural Networks.

In The Last Decade

P. Pajunen

16 papers receiving 498 citations

Peers

P. Pajunen
N. Delfosse France
Pau Bofill Spain
Mika Inki Finland
Geng-Shen Fu United States
Jeanne Rubner Germany
M. Joho Switzerland
Pierce Lai United Kingdom
Donald H. Foley United States
R. Moddemeijer Netherlands
Damien François Belgium
N. Delfosse France
P. Pajunen
Citations per year, relative to P. Pajunen P. Pajunen (= 1×) peers N. Delfosse

Countries citing papers authored by P. Pajunen

Since Specialization
Citations

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

Fields of papers citing papers by P. Pajunen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. Pajunen. 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 P. Pajunen. The network helps show where P. Pajunen may publish in the future.

Co-authorship network of co-authors of P. Pajunen

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

All Works

17 of 17 papers shown
1.
Kortejärvi, Hanna, et al.. (2006). Level A in vitro-in vivo Correlation (IVIVC) Model with Bayesian Approach to Formulation Series. Journal of Pharmaceutical Sciences. 95(7). 1595–1605. 15 indexed citations
2.
Karhunen, Juha & P. Pajunen. (2002). Blind source separation using least-squares type adaptive algorithms. 4. 3361–3364. 11 indexed citations
3.
Pajunen, P.. (2002). Blind separation of binary sources with less sensors than sources. Proceedings of International Conference on Neural Networks (ICNN'97). 3. 1994–1997. 18 indexed citations
4.
Hyvärinen, Aapo & P. Pajunen. (2002). On existence and uniqueness of solutions in nonlinear independent component analysis. 2. 1350–1355. 3 indexed citations
5.
Karhunen, Juha & P. Pajunen. (2002). Blind source separation and tracking using nonlinear PCA criterion: a least-squares approach. Proceedings of International Conference on Neural Networks (ICNN'97). 4. 2147–2152. 5 indexed citations
6.
Joutsensalo, J. & P. Pajunen. (2002). Blind symbol learning algorithms for CDMA system. 1. 152–155. 2 indexed citations
7.
Pajunen, P. & Mark D. Plumbley. (2000). Towards musical instrument separation using multiple-cause neural networks. 5 indexed citations
8.
Hyvärinen, Aapo & P. Pajunen. (1999). Nonlinear independent component analysis: Existence and uniqueness results. Neural Networks. 12(3). 429–439. 268 indexed citations
9.
Koivunen, Visa, P. Pajunen, Juha Karhunen, & Erkki Oja. (1998). Blind separation from ε-contaminated mixtures. European Signal Processing Conference. 1–4. 2 indexed citations
10.
Pajunen, P.. (1998). Blind source separation using algorithmic information theory. Neurocomputing. 22(1-3). 35–48. 34 indexed citations
11.
Karhunen, Juha, P. Pajunen, & Erkki Oja. (1998). The nonlinear PCA criterion in blind source separation: Relations with other approaches. Neurocomputing. 22(1-3). 5–20. 69 indexed citations
12.
Pajunen, P.. (1997). A competitive learning algorithm for separating binary sources.. The European Symposium on Artificial Neural Networks. 5 indexed citations
13.
Pajunen, P. & Juha Karhunen. (1997). Least-Squares Methods for Blind Source Separation Based on Nonlinear PCA. International Journal of Neural Systems. 8(05n06). 601–612. 33 indexed citations
14.
Karhunen, Juha, Andrzej Cichocki, Włodzimierz Kasprzak, & P. Pajunen. (1997). On Neural Blind Separation with Noise Suppression and Redundancy Reduction. International Journal of Neural Systems. 8(2). 219–237. 34 indexed citations
15.
Pajunen, P. & Juha Karhunen. (1997). Self-Organizing Maps for Independent Component Analysis. 2 indexed citations
16.
Karhunen, Juha & P. Pajunen. (1996). Hierarchic Nonlinear PCA Algorithms for Neural Blind Source Separation. 4 indexed citations
17.
Pajunen, P., Aapo Hyvärinen, & Juha Karhunen. (1996). Nonlinear Blind Source Separation by Self-Organizing Maps. 1207–1210. 71 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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