Results 101 to 110 of about 372,370 (292)

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases. [PDF]

Sensors (Basel), 2023
Albiges T, Sabeur Z, Arbab-Zavar B.
europepmc   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

Microphone multiplex system provides multiple outlets from single source [PDF]

, 1966
Microphone multiplex system accepts an audio signal from a single source and provides any number of low impedance outputs at microphone level with complete isolation between output channels.
Lauver, R. E.
core   +1 more source

Autonomous Recognition of Retained Secretions in Central‐Airway Based on Deep Learning for Adult Patients Receiving Invasive Mechanical Ventilation

Advanced Intelligent Systems, EarlyView.
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang, Zhuoran Xiao, Meng Wang, Jianchao Li, Chunjing Tao, Jiangzhen Guo, Yubo Fan   +6 more
wiley   +1 more source

Optical audio signal hiding algorithm based on fractional Fourier transform domain and Gerchberg Saxton phase recovery

Results in Optics
This article proposes an audio signal encryption method based on the Gerchberg-Saxton (G-S) phase recovery algorithm in the fractional Fourier transform domain.
Hang Chen, Zhenduo Ma, Ziyi Zhang, Zhengjun Liu   +3 more
doaj   +1 more source

Hybrid integrated circuits for sound signal processing [PDF]

Tekhnologiya i Konstruirovanie v Elektronnoi Apparature, 2011
Developed hybrid integrated circuit with rated supply voltage of 1,4 V, current consumption 0,7 mA and overall dimensions 8×4×3 mm provides soft processing of the audio signal in analog microelectronic equipment.
Koval’chuk V. A., Sevast’yanov V. V.
doaj  

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

Parametric Coding of Stereo Audio

EURASIP Journal on Advances in Signal Processing, 2005
Parametric-stereo coding is a technique to efficiently code a stereo audio signal as a monaural signal plus a small amount of parametric overhead to describe the stereo image.
Erik Schuijers, Armin Kohlrausch, Steven van de Par, Jeroen Breebaart   +3 more
doaj   +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

Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction

Advanced Intelligent Systems, EarlyView.
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He, Kah Phooi Seng, Chee Shen Lim, Li Minn Ang   +3 more
wiley   +1 more source