Results 221 to 230 of about 779,283 (296)

Compositionality and systematicity emerge from iterated learning in deep linear networks. [PDF]

Proc Natl Acad Sci U S A
Jarvis D, Klein R, Rosman B, Saxe AM.
europepmc   +1 more source

Hardware-Efficient Real-Valued Neural Predistorter for Multimode Power Amplifiers. [PDF]

Sensors (Basel)
Freire LBC, Schuartz L, Lima EG.
europepmc   +1 more source

Dual chaotic encryption method for wireless communication privacy data based on deep learning. [PDF]

PLoS One
Yu H.
europepmc   +1 more source

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Single-Inductor Multiple-Input Multiple-Output Converter With Common Ground, High Scalability, and No Cross-Regulation

IEEE Transactions on Power Electronics, 2021
Single-inductor multiple-input multiple-output (SIMIMO) dc–dc converters can integrate different input sources and supply power to multiple output loads with fewer components. This article proposed a current-source-mode (CSM) SIMIMO dc–dc converter.
Zheng Dong, Xiaolu Lucia Li, Chi K Tse
exaly   +2 more sources

Sampling and Reconstruction of Multiple-Input Multiple-Output Channels

IEEE Transactions on Signal Processing, 2019
Based on the recent development of sampling and reconstruction results for slowly time-varying single-input single-output channel operators, we derive sampling results in the multiple-input multiple-output setting where all subchannels satisfy an underspread condition, that is, their spreading functions are supported on individual sets of small measure.
Dae Gwan Lee, Gotz E Pfander, Volker Pohl   +2 more
exaly   +3 more sources

Maximum Efficiency Formulation for Multiple-Input Multiple-Output Inductive Power Transfer Systems

IEEE Transactions on Microwave Theory and Techniques, 2018
Efficiency maximization based on load optimization has been thoroughly investigated for the conventional single-input single-output (SISO) inductive power transfer (IPT) system.
Quang-Thang Duong, Minoru Okada
exaly   +2 more sources

The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel

IEEE Transactions on Information Theory, 2006
Yossef Steinberg
exaly   +2 more sources

Current Misuses and Future Prospects for Printed Multiple-Input, Multiple-Output Antenna Systems [Wireless Corner]

IEEE Antennas and Propagation Magazine, 2017
Mohammad S Sharawi
exaly   +2 more sources

Hierarchical recursive least squares parameter estimation methods for multiple‐input multiple‐output systems by using the auxiliary models

International Journal of Adaptive Control and Signal Processing, 2023
Multiple‐input multiple‐output (MIMO) models are widely used in practical engineering. This article derives a new identification model of the MIMO system by decomposing the MIMO system into several multiple‐input single‐output subsystems. By means of the
Haoming Xing, Feng Ding, Feng Pan, Erfu Yang   +3 more
semanticscholar   +1 more source

MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition

Neural Information Processing Systems, 2023
With the advent of deep learning, progressively larger neural networks have been designed to solve complex tasks. We take advantage of these capacity-rich models to lower the cost of inference by exploiting computation in superposition.
Nicolas Menet, Michael Hersche, G. Karunaratne, Luca Benini, Abu Sebastian, Abbas Rahimi   +5 more
semanticscholar   +1 more source