Results 111 to 120 of about 20,128 (303)

A Review on Frequency Compensation and Transient Enhancement Schemes of Flipped Voltage Follower LDO Regulators for SoC Applications

IEEE Access
The low dropout (LDO) regulator is an essential circuit in the wireless power module of any portable device. The power management integrated circuits demand low power, high performance LDO regulator.
P. Manikandan, B. Bindu
doaj   +1 more source

Cryogenic Neuromorphic Synaptic Behavior in 180 nm Silicon Transistors for Emerging Computing Systems

Advanced Intelligent Systems, EarlyView.
This study investigates the neuromorphic plasticity behavior of 180 nm bulk complementary metal oxide semiconductor (CMOS) transistors at cryogenic temperatures. The observed hysteresis data reveal a signature of synaptic behavior in CMOS transistors at 4 K.
Fiheon Imroze, Bhavani Yalagala, Naveen Kumar, Mostafa Elsayed, Meraj Ahmad, Robert Graham, Vihar Georgiev, Hadi Heidari, Martin Weides   +8 more
wiley   +1 more source

A push–pull FVF LDO with full‐spectrum PSR and fast transient response

Electronics Letters
A push–pull low‐dropout regulator based on flipped voltage follower is proposed and designed in 65 nm CMOS, which has a push‐current mode and a pull‐current one.
Heng Zheng, Baixin Liu, Chen Wang, Xukun Wang, Bo Zhou   +4 more
doaj   +1 more source

The Effects of ELDRS at Ultra-Low Dose Rates [PDF]

, 2011
We present results on the effects on ELDRS at dose rates of 10, 5, 1, and 0.5 mrad(Si)/s for a variety of radiation hardened and commercial devices. We observed low dose rate enhancement below 10 mrad(Si)/s in several different parts.
Albarian, Rafi, Burns, Samuel, Carts, Martin, Chaumont, Geraldine, Chen, Dakai, Cox, Stephen, Duperray, Herve, Forney, James, Holcombe, Bruce, Kruckmeyer, Kirby, LaBel, Kenneth, Little, Bradley, Ouellet, Al, Pease, Ronald, Phan, Anthony, Salzman, James   +15 more
core   +1 more source

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

Advanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Synthetic Electrocardiogram Spectrogram Generation Using Generative Adversarial Network‐Based Models: A Comparative Study

Advanced Intelligent Systems, EarlyView.
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova, Norelli Schettini, Winston Percybrooks, Begoña García‐Zapirain   +3 more
wiley   +1 more source

A Generalizable Transformer Framework for Gene Regulatory Network Inference from Single‐Cell Transcriptomes

Advanced Intelligent Systems, EarlyView.
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng, Hyobin Kim, Patrick Martin, Junil Kim, Tae‐Hyung Kim, Gi‐Hoon Nam, Dongha Kim, Kyoung Jae Won   +7 more
wiley   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

A Low-Voltage Multistage Output Capacitor-Less LDO Using Dynamic Transient Enhancement Technique for SoC Applications

IEEE Access
This paper introduces a sub-1V output capacitorless low dropout regulator (OCL-LDO) for fast load transients. The OCL-LDO structures a multi-gain stage error amplifier and employs a dynamic transient enhancement (DTE) technique to improve response time ...
T. Nagateja, Ke-Horng Chen, Asisa Panigrahy, Leenendra Chowdary Gunnam, M. Durga Prakash   +4 more
doaj   +1 more source

Rural Facility Electric Power Quality Enhancement [PDF]

, 1991
Electric power disturbances are known to be more prevalent in small, isolated power systems than in larger interconnected grids which service most of the United States. This fact has given rise to a growing concern about the relative merits of different
Aspnes, J.D., Merritt, R.P., Spell, B.D., Wilson, M.   +3 more
core