| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 310 | 38 | 54 | 11 |
Journal of Signal Processing Systems investigates areas of study like Pattern recognition (psychology), Artificial intelligence, Algorithm, Pattern recognition and Field-programmable gate array. Journal of Signal Processing Systems addresses concerns in Pattern recognition (psychology) which are intertwined with other disciplines, such as Artificial neural network, Speech recognition and Computer architecture. Artificial intelligence research presented in the journal encompasses a variety of subjects, including Machine learning and Computer vision.
Algorithm research is concerned with Computation in particular. Most of the Field-programmable gate array studies addressed also intersect with Parallel computing.
The most cited publications mainly tackle studies in Pattern recognition (psychology), Algorithm, Convolutional neural network, Artificial intelligence and Pattern recognition. The published articles hold forums on Pattern recognition (psychology) that merge themes from other disciplines such as Computer architecture, Energy consumption, Speech recognition, Node (networking) and Mobile device. The works on Artificial intelligence tackled in the most cited publications bring together disciplines like Field (computer science), Machine learning and Fault detection and isolation.
The scientific interests tackled in the journal are Pattern recognition (psychology), Artificial intelligence, Algorithm, Pattern recognition and Computer engineering. The studies in Pattern recognition (psychology) featured incorporate elements of Identification (information), Field (computer science), Image (mathematics), Feature extraction and Robustness (computer science). The journal holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning and Computer vision.
Many of the studies tackled connect Algorithm with a similar field of study like Speedup. The studies on Deep learning discussed can also contribute to research in the domains of Object detection and Data mining. Convolutional neural network research discussed connects with the study of Field-programmable gate array.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Signal Processing Systems (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Signal Processing Systems (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 18.38% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.22% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.21% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.41% of all publications and 62.16% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Rajdeep Kumar Nath;Himanshu Thapliyal;Allison Caban-Holt
(2021)Adarsha Balaji;Thibaut Marty;Anup Das;Francky Catthoor
(2020)Zhiqiang Que;Yongxin Zhu;Hongxiang Fan;Jiuxi Meng
(2020)Yi Xie;Zhuohang Li;Cong Shi;Jian Liu
(2021)Pablo Pascual Campo;Vesa Lampu;Alexandre Meirhaeghe;Jani Boutellier
(2020)Dimitrios Stathis;Chirag Sudarshan;Yu Yang;Matthias Jung
(2020)Jean Moraes;Helder Oliveira;Eduardo Cerqueira;Cristiano Both
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