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With an ongoing trend in computing hardware towards increased heterogeneity, domain-specific co-processors are emerging as alternatives to centralized paradigms. The tensor core unit (TPU) has shown to outperform graphic process units by…

Disordered Systems and Neural Networks · Physics 2020-11-24 Mario Miscuglio , Volker J. Sorger

Optical wireless communication (OWC) is a promising technology for future wireless communications owing to its potentials for cost-effective network deployment and high data rate. There are several implementation issues in the OWC which…

Information Theory · Computer Science 2023-12-05 Hoon Lee , Sang Hyun Lee , Tony Q. S. Quek , Inkyu Lee

Convolutional neural networks (CNNs) are representative models of artificial neural networks (ANNs). However, the considerable power consumption and limited computing speed of electrical computing platforms restrict further CNN development…

To guarantee excellent reliability performance in ultra-reliable low-latency communications (URLLC), pragmatic precoder design is an effective approach. However, an efficient precoder design highly depends on the accurate instantaneous…

Information Theory · Computer Science 2023-04-24 Chang Liu , Shuangyang Li , Weijie Yuan , Xuemeng Liu , Derrick Wing Kwan Ng

This letter proposes a design of low peak-to-average power ratio (PAPR), low symbol error rate (SER), and high data rate signal for optical orthogonal frequency division multiplexing (OFDM) systems. The proposed design leverages a…

Systems and Control · Electrical Eng. & Systems 2025-09-12 Nam N. Luong , Chuyen T. Nguyen , Thanh V. Pham

With the increasing demands on future wireless systems, new design objectives become eminent. Low-density parity-check codes together with belief propagation (BP) decoding have outstanding performance for large block lengths. Yet, for…

Information Theory · Computer Science 2024-06-06 Jonathan Mandelbaum , Sisi Miao , Nils Albert Schwendemann , Holger Jäkel , Laurent Schmalen

Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand substantial computational resources, often hindering…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Minho Choi , Jinlin Xiang , Anna Wirth-Singh , Seung-Hwan Baek , Eli Shlizerman , Arka Majumdar

Data protection methods like cryptography, despite being effective, inadvertently signal the presence of secret communication, thereby drawing undue attention. Here, we introduce an optical information hiding camera integrated with an…

Optics · Physics 2024-06-13 Bijie Bai , Ryan Lee , Yuhang Li , Tianyi Gan , Yuntian Wang , Mona Jarrahi , Aydogan Ozcan

Growing diversity and complexity of on-chip photonic applications requires rapid design of components with state-of-the-art operation metrics. Here, we demonstrate a highly flexible and efficient method for designing several classes of…

Optics · Physics 2024-07-16 Mehmet Can Oktay , Emir Salih Magden

Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics, for machine learning algorithms such as neural networks of various types.…

Optics · Physics 2021-01-27 Changming Wu , Heshan Yu , Seokhyeong Lee , Ruoming Peng , Ichiro Takeuchi , Mo Li

Most of the recent power line communication (PLC) systems and standards, both narrow-band and broadband, are based on orthogonal frequency-division multiplexing (OFDM). This multiplexing scheme however suffers from the high peak-to-average…

Signal Processing · Electrical Eng. & Systems 2018-10-17 Bamidele Adebisi , Khaled M. Rabie , Augustine Ikpehai , Cinna Soltanpur , Andrew Wells

The ever-increasing demand for Artificial Intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled…

Emerging Technologies · Computer Science 2021-10-06 Joshua Robertson , Paul Kirkland , Juan Arturo Alanis , Matěj Hejda , Julián Bueno , Gaetano Di Caterina , Antonio Hurtado

Fast Fourier convolution (FFC) is the recently proposed neural operator showing promising performance in several computer vision problems. The FFC operator allows employing large receptive field operations within early layers of the neural…

Sound · Computer Science 2022-04-08 Ivan Shchekotov , Pavel Andreev , Oleg Ivanov , Aibek Alanov , Dmitry Vetrov

The integrated optical circuit is a promising architecture for the realization of complex quantum optical states and information networks. One element that is required for many of these applications is a high-efficiency photon detector…

Ultrafast lasers with simultaneously high average and peak power have become indispensable for driving a multitude of applications, including high-harmonic generation, strong-field physics, and particle source applications. Both parametric…

Diffractive deep neural network (D2NN), known for its high speed and strong parallelism, has been widely applied across various fields, including pattern recognition, image processing, and image transmission. However, existing network…

Applied Physics · Physics 2025-03-24 Peijie Feng , Yong Tan , Mingzhe Chong , Lintao Li , Zongkun Zhang , Fubei Liu , Yunhua Tan , Yongzheng Wen

A multimode optical receiver for free space optical communications (FSOC) based on a photonic lantern and adaptive optics coherent beam combining (CBC) of the lantern's single-mode outputs is proposed and demonstrated for the first time.…

Electroencephalography (EEG) analysis extracts critical information from brain signals, which has provided fundamental support for various applications, including brain-disease diagnosis and brain-computer interface. However, the real-time…

Signal Processing · Electrical Eng. & Systems 2023-01-25 Tao Yan , Maoqi Zhang , Sen Wan , Kaifeng Shang , Haiou Zhang , Xun Cao , Xing Lin , Qionghai Dai

Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN). Unfortunately, the non-linear operations and the high-precision requirements of DNNs…