Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological structures and as promising pattern recognition tools suitable for their implementation in neuromorphic processors, benefited from the modest use of...
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April 10, 2023 (v1)PublicationUploaded on: April 14, 2023
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October 21, 2020 (v1)Publication
Neural networks have enabled great advances in recent times due mainly to improved parallel computing capabilities in accordance to Moore's Law, which allowed reducing the time needed for the parameter learning of complex, multi-layered neural architectures. However, with silicon technology reaching its physical limits, new types of computing...
Uploaded on: December 4, 2022 -
November 14, 2022 (v1)Publication
In recent years, locomotion mechanisms exhibited by vertebrate animals have been the inspiration for the improvement in the performance of robotic systems. These mechanisms include the adaptability of their locomotion to any change registered in the environment through their biological sensors. In this regard, we aim to replicate such kind of...
Uploaded on: March 24, 2023 -
November 14, 2022 (v1)Publication
In recent years, locomotion mechanisms exhibited by vertebrate animals have been the inspiration for the improvement in the performance of robotic systems. These mechanisms include the adaptability of their locomotion to any change registered in the environment through their biological sensors. In this regard, we aim to replicate such kind of...
Uploaded on: March 24, 2023