Quantum tunneling based ultra-compact and energy efficient spiking neuron enables hardware SNN

AK Singh, V Saraswat, MS Baghini… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Low-power and low-area neurons are essential for hardware implementation of large-scale
SNNs. Various novel-physics-based leaky-integrate-and-fire (LIF) neuron architectures have …

SHIP: a computational framework for simulating and validating novel technologies in hardware spiking neural networks

E Gemo, S Spiga, S Brivio - Frontiers in Neuroscience, 2024 - frontiersin.org
Investigations in the field of spiking neural networks (SNNs) encompass diverse, yet
overlapping, scientific disciplines. Examples range from purely neuroscientific …

The spiking neural network based on fMRI for speech recognition

Y Song, L Guo, M Man, Y Wu - Pattern Recognition, 2024 - Elsevier
The structure of the human brain has evolved to achieve extraordinary computing power
through continuous refinement by natural selection. At present, the topology of brain-like …

Real-world performance estimation of liquid state machines for spoken digit classification

AA Kadam, A Biswas, V Saraswat… - … Joint Conference on …, 2023 - ieeexplore.ieee.org
Liquid State Machine (LSM) is a brain-inspired neural network architecture for solving
temporal classification problems like speech recognition. The simple structure of LSM with a …

Spike-train level supervised learning algorithm based on bidirectional modification for liquid state machines

H Lu, X Lin, X Wang, P Du - Applied Intelligence, 2023 - Springer
Liquid state machine (LSM) of spiking neurons is a biologically plausible computational
model imitating the structure and functions of the nervous system for information processing …

MAdapter: A Multimodal Adapter for Liquid State Machines configures the Input Layer for the same Reservoir to enable Vision and Speech Classification

A Biswas, NS Nambiar, K Kejriwal… - 2023 International Joint …, 2023 - ieeexplore.ieee.org
The human cortex is capable of multi-modal processing. Then, assuming that the biological
model of the brain cortex is captured by Liquid State Machines (LSMs), it should be …