Raffaele Parisi

1.8k total citations
65 papers, 1.2k citations indexed

About

Raffaele Parisi is a scholar working on Signal Processing, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Raffaele Parisi has authored 65 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Signal Processing, 27 papers in Computational Mechanics and 21 papers in Artificial Intelligence. Recurrent topics in Raffaele Parisi's work include Speech and Audio Processing (30 papers), Advanced Adaptive Filtering Techniques (26 papers) and Neural Networks and Applications (21 papers). Raffaele Parisi is often cited by papers focused on Speech and Audio Processing (30 papers), Advanced Adaptive Filtering Techniques (26 papers) and Neural Networks and Applications (21 papers). Raffaele Parisi collaborates with scholars based in Italy, United States and Ireland. Raffaele Parisi's co-authors include Elio D. Di Claudio, Aurelio Uncini, Michele Scarpiniti, Danilo Comminiello, G. Orlandi, Bhaskar D. Rao, Gaetano Scarano, Simone Scardapane, Maria Filomena Camões and Massimo Panella and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and Neurocomputing.

In The Last Decade

Raffaele Parisi

60 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raffaele Parisi Italy 17 735 563 307 251 213 65 1.2k
Wasfy B. Mikhael United States 19 670 0.9× 443 0.8× 586 1.9× 236 0.9× 122 0.6× 255 1.5k
Fuliang Yin China 18 552 0.8× 254 0.5× 288 0.9× 190 0.8× 83 0.4× 141 1.2k
T. Aboulnasr Canada 16 949 1.3× 956 1.7× 457 1.5× 98 0.4× 152 0.7× 91 1.6k
Da‐Zheng Feng China 19 553 0.8× 274 0.5× 225 0.7× 206 0.8× 105 0.5× 120 1.1k
Kostas Berberidis Greece 21 396 0.5× 453 0.8× 197 0.6× 143 0.6× 75 0.4× 155 1.5k
José A. Apolinário Brazil 17 788 1.1× 512 0.9× 270 0.9× 115 0.5× 92 0.4× 99 1.1k
Orlando J. Tobias Brazil 14 462 0.6× 553 1.0× 261 0.9× 69 0.3× 143 0.7× 54 865
Shuxue Ding Japan 17 351 0.5× 306 0.5× 325 1.1× 168 0.7× 48 0.2× 127 1.1k
Xiangping Zeng China 19 496 0.7× 536 1.0× 139 0.5× 211 0.8× 203 1.0× 43 879
Jean Jiang United States 13 444 0.6× 520 0.9× 79 0.3× 88 0.4× 263 1.2× 58 900

Countries citing papers authored by Raffaele Parisi

Since Specialization
Citations

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

Fields of papers citing papers by Raffaele Parisi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raffaele Parisi

This figure shows the co-authorship network connecting the top 25 collaborators of Raffaele Parisi. A scholar is included among the top collaborators of Raffaele Parisi 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 Raffaele Parisi. Raffaele Parisi 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.
Frezza, Fabrizio, et al.. (2024). A Generalized Learning Approach to Deep Neural Networks. SHILAP Revista de lepidopterología.
2.
Scarpiniti, Michele, Raffaele Parisi, & Yong-Cheol Lee. (2023). A Scalogram-Based CNN Approach for Audio Classification in Construction Sites. Applied Sciences. 14(1). 90–90. 6 indexed citations
3.
Claudio, Elio D. Di, et al.. (2018). Space Time MUSIC: Consistent Signal Subspace Estimation for Wideband Sensor Arrays. IEEE Transactions on Signal Processing. 66(10). 2685–2699. 47 indexed citations
4.
Lorenzi, Paolo, G. Romano, Rosario Rao, et al.. (2016). Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinson’s Disease. IRIS Research product catalog (Sapienza University of Rome). 152–159. 2 indexed citations
5.
Comminiello, Danilo, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, & Aurelio Uncini. (2015). Improving nonlinear modeling capabilities of functional link adaptive filters. Neural Networks. 69. 51–59. 23 indexed citations
6.
Lorenzi, Paolo, Rosario Rao, G. Romano, et al.. (2015). Smart Sensing Systems for the Detection of Human Motion Disorders. Procedia Engineering. 120. 324–327. 14 indexed citations
7.
Comminiello, Danilo, Michele Scarpiniti, Raffaele Parisi, & Aurelio Uncini. (2013). Intelligent acoustic interfaces for immersive audio. Journal of the Audio Engineering Society. 8 indexed citations
8.
Comminiello, Danilo, Michele Scarpiniti, Raffaele Parisi, & Aurelio Uncini. (2013). Combined adaptive beamforming schemes for nonstationary interfering noise reduction. Signal Processing. 93(12). 3306–3318. 20 indexed citations
9.
Parisi, Raffaele, Maria Filomena Camões, Michele Scarpiniti, & Aurelio Uncini. (2011). Cepstrum Prefiltering for Binaural Source Localization in Reverberant Environments. IEEE Signal Processing Letters. 19(2). 99–102. 18 indexed citations
10.
Scarpiniti, Michele, Danilo Comminiello, Aurelio Uncini, & Raffaele Parisi. (2010). A Functional Link Based Nonlinear Echo Canceller Exploiting Sparsity. 33(9). 3834–43. 10 indexed citations
11.
Parisi, Raffaele, et al.. (2008). Prefiltering Techniques on Consistent Peak Selection for Talker Position Estimation in Reverberant Rooms. IRIS Research product catalog (Sapienza University of Rome). 81–84. 1 indexed citations
12.
Scarpiniti, Michele, et al.. (2008). FLEXIBLE NONLINEAR BLIND SIGNAL SEPARATION IN THE COMPLEX DOMAIN. International Journal of Neural Systems. 18(2). 105–122. 7 indexed citations
13.
Calandrino, R., Antonella Del Vecchio, Annarita Savi, et al.. (2006). DECOMMISSIONING PROCEDURES FOR AN 11 MEV SELF-SHIELDED MEDICAL CYCLOTRON AFTER 16 YEARS OF WORKING TIME. Health Physics. 90(6). 588–596. 14 indexed citations
14.
Claudio, Elio D. Di, Raffaele Parisi, & G. Orlandi. (2002). LS-based training algorithm for neural networks. 1. 22–29.
15.
Claudio, Elio D. Di, Raffaele Parisi, & G. Orlandi. (2002). A clustering approach to multi-source localization in reverberant rooms. IRIS Research product catalog (Sapienza University of Rome). 2. 198–201. 2 indexed citations
16.
Claudio, Elio D. Di, Raffaele Parisi, & G. Orlandi. (2002). Discriminative learning strategy for efficient neural decision feedback equalizers. IRIS Research product catalog (Sapienza University of Rome). 4. 521–524. 1 indexed citations
17.
Bucciarelli, T., Giuseppe Fedele, & Raffaele Parisi. (2002). Neural networks based signal detection. 814–818. 3 indexed citations
18.
Parisi, Raffaele, et al.. (2001). BLIND SOURCE SEPARATION IN NONLINEAR MIXTURES BY ADAPTIVE SPLINE NEURAL NETWORKS. IRIS Research product catalog (Sapienza University of Rome). 7 indexed citations
19.
Claudio, Elio D. Di, Raffaele Parisi, & G. Orlandi. (2000). Discriminative learning for neural decision feedback equalizers.. IRIS Research product catalog (Sapienza University of Rome). 219–226. 1 indexed citations
20.
Parisi, Raffaele, Elio D. Di Claudio, G. Orlandi, & Bhaskar D. Rao. (1996). A generalized learning paradigm exploiting the structure of feedforward neural networks. IEEE Transactions on Neural Networks. 7(6). 1450–1460. 60 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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