Results 61 to 70 of about 541,388 (266)

Study of Energy-Efficient Distributed RLS-based Learning with Coarsely Quantized Signals [PDF]

arXiv, 2020
In this work, we present an energy-efficient distributed learning framework using coarsely quantized signals for Internet of Things (IoT) networks. In particular, we develop a distributed quantization-aware recursive least squares (DQA-RLS) algorithm that can learn parameters in an energy-efficient fashion using signals quantized with few bits while ...
arxiv  

Multi‐Diseases Detection with Memristive System on Chip

Advanced Intelligent Systems, EarlyView.
A robust disease detection system, which is capable of the early prevention of acute myocardial infarction and the detection of liver cancer, is implemented on a memristive system‐on‐chip (SoC). A fully integrated SoC is utilized to ensure the system's portability, low latency, high accuracy, and energy efficiency for medical analysis.
Zihan Wang, Daniel W. Yang, Zerui Liu, Evan Yan, Heming Sun, Ning Ge, Miao Hu, Wei Wu   +7 more
wiley   +1 more source

Electromagnetically Adhering and Self‐Inductive Sensing Claw for Continuum Climbing Robots: Design, Control, and Applications

Advanced Intelligent Systems, EarlyView.
To argue the applicability of continuum wall‐climbing robots in the nuclear industry, an electromagnetic adhering and self‐inductive sensing integrated claw is developed. The flexible claw realizes an integrated design of the physical structure and excitation circuit. An automatic contact strategy based on fuzzy controller is established, which enables
Pengpeng Yang, Jialin Zang, Bo Huang, Jianwen Zhao   +3 more
wiley   +1 more source

Artificial Intelligence‐Enhanced, Closed‐Loop Wearable Systems Toward Next‐Generation Diabetes Management

Advanced Intelligent Systems, EarlyView.
Recent advancements in wearable healthcare have brought accessible continuous glucose monitoring systems (CGMs) for diabetes management. To address the limitations of CGMs, closed‐loop systems utilizing monitored glucose levels for insulin dosing are being developed.
Wei Huang, Ivo Pang, Jing Bai, Binbin Cui, Xiaojuan Qi, Shiming Zhang   +5 more
wiley   +1 more source

Error Decay of (almost) Consistent Signal Estimations from Quantized Gaussian Random Projections [PDF]

arXiv, 2014
This paper provides new error bounds on "consistent" reconstruction methods for signals observed from quantized random projections. Those signal estimation techniques guarantee a perfect matching between the available quantized data and a new observation of the estimated signal under the same sensing model.
arxiv  

Reconstruction Condition of Quantized Signals in Unlimited Sampling Framework [PDF]

arXiv, 2020
The latest theoretical advances in the field of unlimited sampling framework (USF) show the potential to avoid clipping problems of analog-to-digital converters (ADC). To date, most of the related works have focused on real-valued modulo samples, but little has been reported about the impact of quantization.
arxiv  

Energy‐Efficient Online Training with In Situ Parallel Computing on Electrochemical Memory Arrays

Advanced Intelligent Systems, EarlyView.
By leveraging the intrinsic functionalities of electrochemical random‐access memory, the conductance response to pulse amplitude and quantity enables stochastic multiplication and parallel outer‐product operations between two vectors. This approach significantly accelerates weight gradient computations while reducing time complexity, latency, and ...
Yingming Lu, Zhen Yang, Yaoyu Tao, Lei Cai, Teng Zhang, Longhao Yan, Ru Huang, Yuchao Yang   +7 more
wiley   +1 more source

Voltage‐Summation‐Based Compute‐in‐Memory Technology with Capacitive Synaptic Devices

Advanced Intelligent Systems, EarlyView.
Compute‐in‐memory (CIM) technologies leveraging capacitive coupling offer significant advantages in energy efficiency and IR‐drop elimination. This work introduces voltage‐summation‐based CIM technology, employing capacitive synaptic devices for matrix–vector multiplication.
Jung Nam Kim, Yong Woo Kim, Boram Kim, Doo‐Hyun Kim, Gil Sung Lee, Dong‐Hyuk Chae, Minkyu Je, Minsuk Koo, Yoon Kim   +8 more
wiley   +1 more source

Joint Sequential Fronthaul Quantization and Hardware Complexity Reduction in Uplink Cell-Free Massive MIMO Networks [PDF]

arXiv
Fronthaul quantization causes a significant distortion in cell-free massive MIMO networks. Due to the limited capacity of fronthaul links, information exchange among access points (APs) must be quantized significantly. Furthermore, the complexity of the multiplication operation in the base-band processing unit increases with the number of bits of the ...
arxiv  

Distributed Quantization for Sparse Time Sequences [PDF]

arXiv, 2019
Analog signals processed in digital hardware are quantized into a discrete bit-constrained representation. Quantization is typically carried out using analog-to-digital converters (ADCs), operating in a serial scalar manner. In some applications, a set of analog signals are acquired individually and processed jointly.
arxiv