28 citations · 46 across the 12 of their papers we have counts for
4 papers · 1 filter
Training Spiking Neural Networks via Augmented Direct Feedback Alignment
Yongbo Zhang, Katsuma Inoue, Mitsumasa Nakajima +3
Spiking neural networks (SNNs), the models inspired by the mechanisms of real neurons in the brain, transmit and represent information by employing discrete action potentials or sp…
How noise affects memory in linear recurrent networks
JingChuan Guan, Tomoyuki Kubota, Yasuo Kuniyoshi +1
The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous st…
Informational Embodiment: Computational role of information structure in codes and robots
Alexandre Pitti, Kohei Nakajima, Yasuo Kuniyoshi
The body morphology plays an important role in the way information is perceived and processed by an agent. We address an information theory (IT) account on how the precision of sen…
Exploiting Chaotic Dynamics as Deep Neural Networks
Shuhong Liu, Nozomi Akashi, Qingyao Huang +2
Chaos presents complex dynamics arising from nonlinearity and a sensitivity to initial states. These characteristics suggest a depth of expressivity that underscores their potentia…