Titlebook: Reservoir Computing; Theory, Physical Imp Kohei Nakajima,Ingo Fischer Book 2021 Springer Nature Singapore Pte Ltd. 2021 Reservoir Computing

Adornment

tool for clinicians, pathologists, and basic scientists who wish to understand, apply, and investigate the multiple new aspects of melanoma genetics..978-1-4939-8076-5978-1-4939-3554-3Series ISSN 2626-1456 Series E-ISSN 2626-1464

coagulation

1619-7127 ir respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamic978-981-13-1687-6Series ISSN 1619-7127 Series E-ISSN 2627-6461

SCORE

Reservoirs Learn to Learn of any concrete task that is likely to be essential for the survival of the organism. We apply the Learning-to-Learn (L2L) paradigm to mimic this two-tier process, where a set of (hyper)parameters of the reservoir are optimized for a whole family of learning tasks. We found that this substantially

Gourmet

Reservoir Computing Using Autonomous Boolean Networks Realized on Field-Programmable Gate Arraysat high speed, leading to the possibility of full-image classification on the nanosecond time scale. We explore the dynamics of the autonomous Boolean networks in response to injected signals and, based on these results, investigate the performance of the reservoir computer on the written-digit task