Results 101 to 110 of about 3,785,484 (384)

An efficient watermarking algorithm for digital audio data in security applications. [PDF]

Sci Rep, 2023
Yamni M, Daoui A, Karmouni H, Sayyouri M, Qjidaa H, Motahhir S, Jamil O, El-Shafai W, Algarni AD, Soliman NF, Aly MH.   +10 more
europepmc   +1 more source

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

Audio Codec Using Legendre Functions for Simplified Digital Telephony [PDF]

, 2021
S. Ananthi, A.J. Arun, Sivakannan Subramani, Krishnasamy Padmanabhan   +3 more
openalex   +1 more source

Composing with Sounds: Designing an Object-Oriented DAW for the Teaching of Sound-Based Composition [PDF]

, 2019
This paper presents and discusses the ComposeWith Sounds (CwS) Digital AudioWorkstation (DAW) and its approach to sequencing musical materials. The system is designed to facilitate the composition within the realm of Sound-based music wherein sound ...
Chapman, Duncan, Eniu, Mihai, Holland, David, Landy, Leigh, Pearse, Stephen   +4 more
core  

What Healthcare Workers Told Us about Working through the COVID-19 Pandemic: A Qualitative Analysis of Digital Audio Stories. [PDF]

J Nurs Manag, 2023
Grobbel C, Lackman Zeman L, Homayouni R, Roy S, Kenney FE, Mulhem E.   +5 more
europepmc   +1 more source

QS4D: Quantization‐Aware Training for Efficient Hardware Deployment of Structured State‐Space Sequential Models

Advanced Intelligent Systems, EarlyView.
Quantization‐aware training creates resource‐efficient structured state space sequential S4(D) models for ultra‐long sequence processing in edge AI hardware. Including quantization during training leads to efficiency gains compared to pure post‐training quantization.
Sebastian Siegel, Ming‐Jay Yang, Younes Bouhadjar, Maxime Fabre, Emre Neftci, John Paul Strachan   +5 more
wiley   +1 more source

The switching and learning behavior of an octopus cell implemented on FPGA

Mathematical Biosciences and Engineering
A dendrocentric backpropagation spike timing-dependent plasticity learning rule has been derived based on temporal logic for a single octopus neuron.
Alexej Tschumak, Frank Feldhoff , Frank Klefenz   +2 more
doaj   +1 more source

Analysis of the Single Frequency Network Gain in Digital Audio Broadcasting Networks. [PDF]

Sensors (Basel), 2021
Staniec K.
europepmc   +1 more source

ControlIt: A Universal Framework for Translational, Adaptive, and Online Brain–Computer Interfaces

Advanced Intelligent Systems, EarlyView.
Brain–computer interfaces (BCIs) lack a unified platform that works across signals and algorithms. ControlIt, an open‐source, modular ROS2‐based BCI framework supporting electroencephalography (EEG), electrocorticography (ECoG), and spike‐based decoding across both classification and regression tasks is presented.
Wanlin Yang, Chenyang Li, Xinxiu Xu, Xindong Wang, Yongcheng Guo, Xiaoke Chai, Tianqin Cao, Jiuxiang Song, Nan Wang, Xueming Zhang, Yi Yang, Cong Zheng, He Cui   +12 more
wiley   +1 more source

Testing high resolution SD ADC’s by using the noise transfer function [PDF]

, 2004
A new solution to improve the testability of high resolution SD Analogue to Digital Converters (SD ADC’s) using the quantizer input as test node is described.
De-Venuto, Daniela, Richardson, Andrew
core