Article
Engineering, Electrical & Electronic
Joon-Kyu Han, Myung-Su Kim, Seung-Il Kim, Mun-Woo Lee, Sang-Won Lee, Ji-Man Yu, Yang-Kyu Choi
Summary: The leaky characteristic of a 1T-neuron can be controlled by adjusting the relative position of the drain junction to the gate, tuning the gate voltage, and modulating the body doping concentration, which accelerates band-to-band tunneling.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2021)
Article
Physics, Applied
Namita Bindal, Ravish Kumar Raj, Brajesh Kumar Kaushik
Summary: This paper proposes a neuron device based on AFM skyrmions, which exhibits the leaky-integrate-fire functionality. By utilizing current-driven skyrmion dynamics on shape-configured nanotracks, high-speed and energy-efficient neuromorphic computing can be achieved.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2022)
Article
Engineering, Electrical & Electronic
Jiaming Lin, Weixi Ye, Xianghong Zhang, Qiming Lian, Shengyuan Wu, Tailiang Guo, Huipeng Chen
Summary: In this study, an artificial neuron device based on Ag/TaOx/Si material was proposed, which exhibited good characteristics and successfully simulated the LIF neuron model. The increase of oxygen vacancy concentration was found to significantly improve the performance of artificial neurons.
IEEE ELECTRON DEVICE LETTERS
(2022)
Article
Computer Science, Theory & Methods
Ioannis E. Venetis, Astero Provata
Summary: This study analyzes the performance issues of implementing the coupled Leaky Integrate-and-Fire model on a GPU, finding that the problem is mainly memory-bound. The results demonstrate that using advanced memory technology on a GPU can achieve better performance.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Effrosyni Doutsi, Lionel Fillatre, Marc Antonini, Panagiotis Tsakalides
Summary: This paper introduces a novel coding/decoding mechanism named Dual-SIM quantizer (Dual-SIMQ) that simulates one of the most important properties of the human visual system to enhance the quality of visual perception. By utilizing neuroscience models, the Dual-SIMQ combines time-SIM and rate-SIM mechanisms to achieve high-quality neural coding and simple decoding, ultimately improving the reconstruction quality and performance of the visual stimulus. The proposed mechanism shows promising results in controlling reconstruction accuracy, numerical comparison with state-of-the-art methods, and enhancing perceptual reconstruction quality.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Mathematics, Interdisciplinary Applications
Ciyan Zheng, Long Peng, Jason K. K. Eshraghian, Xiaoli Wang, Jian Cen, Herbert Ho-Ching Iu
Summary: This study presents a novel floating flux-controlled memcapacitor design that can be used for experimental verification of large-scale memcapacitor arrays. By dynamically modifying the membrane time constant, the memcapacitor brings about novel short-term memory dynamics.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2022)
Article
Computer Science, Information Systems
Natasa M. Samardzic, Jovan S. Bajic, Dalibor L. Sekulic, Stanisa Dautovic
Summary: This paper proposes and simulates a circuit implementation of a leaky integrate-and-fire neuron model with a volatile memristor. The model is capable of mimicking spatial and temporal integration, firing function, and signal decay, which facilitates the design of complex memristive neural networks.
Article
Engineering, Electrical & Electronic
Faisal Bashir, Furqan Zahoor, Ali S. Alzahrani, Abdul Raouf Khan
Summary: This paper proposes a leaky integrate and fire (LIF) neuron design based on a Schottky Barrier MOSFET (SB-MOSFET) using the Impact Ionization mechanism, which demonstrates considerable improvements in area, energy, and cost. Through 2D calibrated simulation, it is confirmed that the SB-MOSFET LIF neuron is able to precisely replicate the behavior of a neuron without the need for external circuitry. The proposed LIF neuron shows significantly lower energy consumption per spike, approximately 4 pJ/spike, which is the lowest among single transistor-based neurons reported in the literature. Furthermore, it achieves a recognition precision of 89.2% for Modified National Institute of Standards and Technology (MNIST) images. In addition, the SB-MOSFET does not require any doped regions, enabling fabrication with a low thermal budget.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Mathematics
Ghinwa El Masri, Asma Ali, Waad H. Abuwatfa, Maruf Mortula, Ghaleb A. Husseini
Summary: This research compares two methods for estimating the behavior of neurons using the leaky integrate and fire model. The findings show that Heun's method is faster and more accurate, making it more suitable for this model.
Article
Multidisciplinary Sciences
Di Wang, Ruifeng Tang, Huai Lin, Long Liu, Nuo Xu, Yan Sun, Xuefeng Zhao, Ziwei Wang, Dandan Wang, Zhihong Mai, Yongjian Zhou, Nan Gao, Cheng Song, Lijun Zhu, Tom Wu, Ming Liu, Guozhong Xing
Summary: A new type of spiking neuron with leaky-integrate-fire and self-reset (LIFT) characteristics is achieved by manipulating the magnetic domain wall motion in a synthetic antiferromagnetic (SAF) heterostructure. The spintronic LIFT neurons demonstrate high firing rate (up to 17 MHz) and low energy consumption (486 fJ/spike), and a spiking neuron circuit is implemented with fast latency (170 ps) and low power consumption (90.99 mu W). A two-layer spiking neural network based on these spintronic LIFT neurons achieves 88.5% accuracy on the handwritten digit database benchmark.
NATURE COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Akira Goda, Chihiro Matsui, Ken Takeuchi
Summary: An analytical model for stochastic leaky-integrate-and-fire neurons with floating gate technology has been developed. The study explores the stochastic behaviors and population coding of these neurons. It is found that the shape of the inter spike interval distribution can be controlled, improving the population output signal-to-noise ratio and enabling fast computation.
IEEE JOURNAL OF THE ELECTRON DEVICES SOCIETY
(2022)
Article
Engineering, Electrical & Electronic
Mudasir A. Khanday, Faisal Bashir, Farooq A. Khanday
Summary: In this work, a single transistor based on germanium (Ge) is used to construct a leaky integrate-and-fire (LIF) neuron, providing significant improvements in energy efficiency, area efficiency, and reduction in cost. Through 2-D calibrated simulation, it is validated that the Ge-mosfet LIF neuron accurately imitates the behavior of a neuron. The Ge-mosfet exhibits low breakdown voltage, high impact ionization coefficient, and sharp breakdown, contributing to low energy per spike and higher spiking current. Compared to a recently reported silicon-based silicon-on-insulator (SOI) mosfet, the proposed Ge-mosfet LIF neuron requires only 8 pJ/spike of energy. The use of gate voltage allows for controllable firing of the Ge-mosfet LIF neuron, improving the energy efficiency of the spiking neural network (SNN) by inducing sparse action.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2022)
Article
Engineering, Electrical & Electronic
Nguyen T. Thao, Dominik Rzepka, Marek Miskowicz
Summary: Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer function that is being explored as a technique for event-based sampling in data acquisition. This article investigates the retrieval of input from LIF-encoded output by treating LIF output as a transformation of input through a known linear operator. The signal reconstruction method of projection onto convex sets (POCS) is shown to converge to a weighted pseudo-inverse of the operator, allowing for perfect recovery, minimum-norm reconstruction, and improved noise shaping of time quantization.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Materials Science, Multidisciplinary
Bingyang Xie, Xuelian Zhang, Siqi Cheng, Wenjing Jie
Summary: In this study, the resistive switching behaviors in 2D BiOX nanosheets were systematically investigated, with BiOBr nanosheet demonstrating non-volatile bipolar RS behaviors and BiOBr0.7Cl0.3 nanosheet showing volatile threshold switching behaviors. These findings provide a new material foundation for research on novel memory devices and biomimetic synapses.
MATERIALS & DESIGN
(2022)
Article
Biology
Addolorata Marasco, Emiliano Spera, Vittorio De Falco, Annalisa Iuorio, Carmen Alina Lupascu, Sergio Solinas, Michele Migliore
Summary: In this study, an adaptive generalized leaky integrate-and-fire model is proposed to simulate the firing dynamics of hippocampal neurons. By using nonlinear and more realistic initial and update conditions, along with linear ordinary differential equations, the model is able to successfully reproduce the complex and highly variable firing dynamics of neurons.
BULLETIN OF MATHEMATICAL BIOLOGY
(2023)
Article
Optics
Lizhuo Zheng, Shilin Xiao, Zhiyang Liu, Mable P. Fok, Jiafei Fang, Hang Yang, Ming Lu, Zhiyi Zhang, Weisheng Hu
Article
Chemistry, Analytical
Mei Yang, Qidi Liu, Hamza Sayed Naqawe, Mable P. Fok
Review
Chemistry, Multidisciplinary
Qidi Liu, Mable P. Fok
APPLIED SCIENCES-BASEL
(2020)
Editorial Material
Chemistry, Multidisciplinary
Ivana Gasulla, Mable P. Fok
APPLIED SCIENCES-BASEL
(2020)
Article
Engineering, Electrical & Electronic
Qidi Liu, Mable P. Fok
IEEE PHOTONICS JOURNAL
(2020)
Article
Optics
Qidi Liu, Mable P. Fok
Article
Optics
Qidi Liu, Mable P. Fok
Summary: Camouflage is utilized by animals and RF systems for protection and security. The camouflage skills of marine hatchetfish provide survival advantages, which researchers have successfully applied to optical fiber transmission.
Article
Engineering, Electrical & Electronic
Lizhuo Zheng, Zhiyi Zhang, Mable P. Fok, Zhiyang Liu, Shilin Xiao
Summary: An optical analog noise encryption system with adaptive recovery of two-dimensional keys is proposed and demonstrated, achieving successful decryption of encrypted signals using the RT adaptive algorithm at the receiver, showing excellent performance in the experiment.
IEEE PHOTONICS TECHNOLOGY LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Qidi Liu, Benjamin Gily, Mable P. Fok
Summary: Photonics-based frequency estimation approaches offer advantages in increasing operation frequency range, providing rapid measurement response, and improving immunity to electromagnetic interference, which can help overcome limitations of electronic-based systems and enhance measurement precision and system adaptability.
IEEE PHOTONICS TECHNOLOGY LETTERS
(2021)
Article
Optics
S. P. Kulik, K. S. Kravtsov, S. N. Molotkov
Summary: This paper analyzes the relationship between Fock states with different numbers of photons and pure coherent states with random phases, and discusses the experimental resources required to prepare Fock states with specific photon numbers from superposition of Fock states. Optical schemes for implementing PNS attack are provided, and estimates of experimental parameters at which the attack is possible are made.
LASER PHYSICS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Md Asaduzzaman Jabin, Mable P. Fok
Summary: In this study, a feed-forward multilayer perceptron in a deep learning-based artificial neural network (ANN) is proposed to accurately predict 12 optical parameters of silica-based photonic crystal fiber (PCF) using only 6 input parameters. The optimized ANN with 3 hidden layers and 50 neurons in each layer achieves high accuracy and significantly faster prediction compared to conventional numerical simulation methods.
IEEE PHOTONICS TECHNOLOGY LETTERS
(2022)
Article
Optics
Md Asaduzzaman Jabin, Mable P. Fok
Summary: In this Letter, an unsupervised-learning platform-generative adversarial network (GAN) is proposed for experimental data augmentation in a deep-learning assisted photonic-based instantaneous microwave frequency measurement (IFM) system. The GAN can augment the small amount of data into 5000 sets for training the deep learning model, reducing the need for experimental data by 98.75% and improving measurement error by 10 times.
Article
Optics
P. M. Vinetskaya, K. S. Kravtsov, N. A. Borshchevskaia, A. N. Klimov, S. P. Kulik
Summary: This paper reviews possible realizations of entanglement-based QKD and assesses their feasibility in terms of implementation complexity and provided security. It also proposes a novel active basis choice approach that enables to use only one single-photon detector per user. The paper provides all necessary details including the required electro-optic crystal configurations to implement such a scheme experimentally.
LASER PHYSICS LETTERS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Lizhuo Zheng, Zhiyang Liu, Shilin Xiao, Zhiyi Zhang, Qidi Liu, Mable P. Fok
2020 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC)
(2020)
Article
Optics
K. S. Kravtsov, A. K. Zhutov, S. P. Kulik
