Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Ashwin Lele"'
Publikováno v:
IEEE Transactions on Cognitive and Developmental Systems. 14:1092-1103
Learning to adapt one’s gait with environmental changes plays an essential role in locomotion of legged robots which remains challenging for constrained computing resources and energy budget, as in the case of edge-robots. Recent advances in bio-in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c916527685ed923470714a70c683cd2
https://doi.org/10.1109/tcds.2021.3097675
https://doi.org/10.1109/tcds.2021.3097675
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 10:536-545
Online learning for the legged robot locomotion under performance and energy constraints remains to be a challenge. Methods such as stochastic gradient, deep reinforcement learning (RL) have been explored for bipeds, quadrupeds and hexapods. These te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1be69fa8c3c21d597800a40755131c12
https://doi.org/10.1109/jetcas.2020.3033135
https://doi.org/10.1109/jetcas.2020.3033135
Publikováno v:
2022 Opportunity Research Scholars Symposium (ORSS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8fa926ab1b30b77188d358bd934e9d7b
https://doi.org/10.1109/orss55359.2022.9806037
https://doi.org/10.1109/orss55359.2022.9806037
Autor:
Ashwin Lele, Srivatsava Jandhyala, Saurabh Gangurde, Virendra Singh, Sreenivas Subramoney, Udayan Ganguly
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031215131
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5be9526a893822890a85c81380db5759
https://doi.org/10.1007/978-3-031-21514-8_41
https://doi.org/10.1007/978-3-031-21514-8_41
Publikováno v:
IEEE Electron Device Letters. 40:850-853
Spike time dependent plasticity (STDP) is a learning rule in biology, where the time-correlation of narrow pre- and post-synaptic spikes ( ${t}_{{\text {spike}}} {\approx 5ms}$ ) is tracked across a wide learning window ( ${LW}$ ) of time ( ${t}_{{LW
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dc3919abd93563489548e25292037a8
https://doi.org/10.1109/led.2019.2914406
https://doi.org/10.1109/led.2019.2914406
Publikováno v:
ISCAS
On-chip implementation of spike-time dependent plasticity in spiking neural networks using RRAM synapses requires pulse shaping circuits (PSC) to drive RRAMs. PSCs convert the temporal separation between pre and post neuron spikes to appropriate volt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec3fc113d258e9cb6d4f91f7bfd9a6ae
https://doi.org/10.1109/iscas45731.2020.9180803
https://doi.org/10.1109/iscas45731.2020.9180803
Publikováno v:
AICAS
Learning to walk -- i.e., learning locomotion under performance and energy constraints continues to be a challenge in legged robotics. Methods such as stochastic gradient, deep reinforcement learning (RL) have been explored for bipeds, quadrupeds and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62896e5bdd5607ccae4b2893a3cd0c2a
https://doi.org/10.1109/aicas48895.2020.9073987
https://doi.org/10.1109/aicas48895.2020.9073987
Publikováno v:
IJCNN
Learning how to walk is a sophisticated neurological task for most animals. In order to walk, the brain must synthesize multiple cortices, neural circuits, and diverse sensory inputs. Some animals, like humans, imitate surrounding individuals to spee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ff0a04f84c85db877a0b827a54795d1
Publikováno v:
IEEE Electron Device Letters. 39:1159-1162
Physically unclonable functions (PUF) are essential for hardware identity and security for IoT devices. The PUF consists of a multi-bit string that requires unbiased randomness. A one-time programmable memory (OTPM) uses insulator breakdown in metal-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e2c694478cff99ec3de71b579ee388a
https://doi.org/10.1109/led.2018.2844557
https://doi.org/10.1109/led.2018.2844557
Publikováno v:
2018 4th IEEE International Conference on Emerging Electronics (ICEE).
Gradual synaptic weight change is a challenge for realistic RRAM, where SET is normally abrupt. Hence, an attractive RESET only learning scheme is demonstrated with a simple circuit implementation. However, the performance is highly sensitive to prog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e90e92db7d4e3de357a43e3238612f12
https://doi.org/10.1109/icee44586.2018.8937982
https://doi.org/10.1109/icee44586.2018.8937982