Zobrazeno 1 - 10
of 422
pro vyhledávání: '"Liquid state machine"'
Autor:
Oscar I. Alvarez-Canchila, Andres Espinal, Marco A. Sotelo-Figueroa, Jorge A. Soria-Alcaraz, Horacio Rostro-Gonzalez
Publikováno v:
IEEE Access, Vol 12, Pp 182856-182871 (2024)
The Liquid State Machine (LSM) framework addresses supervised learning tasks involving spatio-temporal data streams. It relies on a randomly created, untrained Spiking Recurrent Neural Network (SRNN), called the “liquid,” to map inputs into task-
Externí odkaz:
https://doaj.org/article/bb23b486e8c44eafb55f9adc6c146060
Publikováno v:
IEEE Access, Vol 11, Pp 50180-50194 (2023)
The nonlinear inverted pendulum model of a lightweight bipedal robot is identified in real-time using a reservoir-based Recurrent Neural Network (RNN). The adaptation occurs online, while a disturbance force is repeatedly applied to the robot body. T
Externí odkaz:
https://doaj.org/article/9e8f58f7314c4ceca0b8c66bf305e0c3
Publikováno v:
Frontiers in Neuroinformatics, Vol 17 (2023)
In this study, we explore the simulation setup in computational neuroscience. We use GENESIS, a general purpose simulation engine for sub-cellular components and biochemical reactions, realistic neuron models, large neural networks, and system-level
Externí odkaz:
https://doaj.org/article/bff387a08b3644e89cc1a9b6ab8a9c55
Autor:
Sorin VLAD, Ionel GORDIN
Publikováno v:
Journal of Applied Computer Science & Mathematics, Vol 15, Iss 2, Pp 44-48 (2021)
A general problem occurring when training the recurrent neural networks (RNN) is that the solution space is extensive and the chance of choosing a local minimum instead of a global minimum is high. This is due to the fact that the weights among the n
Externí odkaz:
https://doaj.org/article/7a1d6a119649475bb424ba19245cb155
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
A liquid state machine (LSM) is a biologically plausible model of a cortical microcircuit. It exists of a random, sparse reservoir of recurrently connected spiking neurons with fixed synapses and a trainable readout layer. The LSM exhibits low traini
Externí odkaz:
https://doaj.org/article/bf13ca09ba91412487a106315593b9d1
Akademický článek
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Publikováno v:
Algorithms, Vol 16, Iss 9, p 430 (2023)
Scene understanding is one of the most challenging areas of research in the fields of robotics and computer vision. Recognising indoor scenes is one of the research applications in the category of scene understanding that has gained attention in rece
Externí odkaz:
https://doaj.org/article/57a326ca54b94726b35d8900bc885e94
Autor:
Steven A. Frank
Publikováno v:
Entropy, Vol 25, Iss 8, p 1162 (2023)
Organisms perceive their environment and respond. The origin of perception–response traits presents a puzzle. Perception provides no value without response. Response requires perception. Recent advances in machine learning may provide a solution. A
Externí odkaz:
https://doaj.org/article/97e34dc6b0de4f7eb7d91cb059c86771
Autor:
Alberto Patiño-Saucedo, Horacio Rostro-González, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
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 sui
Externí odkaz:
https://doaj.org/article/8f541b3e28974c9ca7f53f5639e2986b
Publikováno v:
Applied Sciences, Vol 12, Iss 20, p 10484 (2022)
Lipreading refers to the task of decoding the text content of a speaker based on visual information about the movement of the speaker’s lips. With the development of deep learning in recent years, lipreading has attracted extensive research. Howeve
Externí odkaz:
https://doaj.org/article/418d7e7e32544139b318a5c9fe065317