Accelerating the convergence of the back-propagation method
- Journal
- Biological Cybernetics
In The Last Decade
doi.org/10.1007/bf00332914 →Countries where authors are citing Accelerating the convergence of the back-propagation method
This map shows the geographic impact of Accelerating the convergence of the back-propagation method. 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 Accelerating the convergence of the back-propagation method with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Accelerating the convergence of the back-propagation method more than expected).
Fields of papers citing Accelerating the convergence of the back-propagation method
This network shows the impact of Accelerating the convergence of the back-propagation method. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Accelerating the convergence of the back-propagation method.
About Accelerating the convergence of the back-propagation method
This paper, published in 1988, received 812 indexed citations . Written by Thomas P. Vogl, A. K. Rigler and Daniel L. Alkon covering the research area of Artificial Intelligence and Signal Processing. It is primarily cited by scholars working on Artificial Intelligence (381 citations), Control and Systems Engineering (134 citations) and Computer Vision and Pattern Recognition (134 citations). Published in Biological Cybernetics.
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.
This paper is also available at doi.org/10.1007/bf00332914.