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Analysis of institutional authors

Zamacola RAuthorOtero AAuthorDe La Torre EAuthor

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June 12, 2020
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Article
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A dynamically reconfigurable BBNN architecture for scalable neuroevolution in hardware

Publicated to: Electronics. 9 (5): - 2020-05-01 9(5), DOI: 10.3390/electronics9050803

Authors:

García A; Zamacola R; Otero A; de la Torre E
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Affiliations

Electrónica Industrial. Universidad Politécnica de Madrid - Author
Universidad Autónoma de Madrid - Author

Abstract

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In this paper, a novel hardware architecture for neuroevolution is presented, aiming to enable the continuous adaptation of systems working in dynamic environments, by including the training stage intrinsically in the computing edge. It is based on the block-based neural network model, integrated with an evolutionary algorithm that optimizes the weights and the topology of the network simultaneously. Differently to the state-of-the-art, the proposed implementation makes use of advanced dynamic and partial reconfiguration features to reconfigure the network during evolution and, if required, to adapt its size dynamically. This way, the number of logic resources occupied by the network can be adapted by the evolutionary algorithm to the complexity of the problem, the expected quality of the results, or other performance indicators. The proposed architecture, implemented in a Xilinx Zynq-7020 System-on-a-Chip (SoC) FPGA device, reduces the usage of DSPs and BRAMS while introducing a novel synchronization scheme that controls the latency of the circuit. The proposed neuroevolvable architecture has been integrated with the OpenAI toolkit to show how it can efficiently be applied to control problems, with a variable complexity and dynamic behavior. The versatility of the solution is assessed by also targeting classification problems.
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Keywords

Block-based neural networkDynamic and partial reconfigurationNeuroevolutionReinforcement learningScalability

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Electronics due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2020, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Signal Processing. Notably, the journal is positioned en el Cuartil Q3 for the agency WoS (JCR) in the category Engineering, Electrical & Electronic.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-04:

  • Google Scholar: 5
  • WoS: 1
  • Scopus: 3
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-04:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 19 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Garcia A) and Last Author (TORRE ARNANZ, EDUARDO DE LA).

the author responsible for correspondence tasks has been Garcia A.

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