Results 131 to 140 of about 21,889,530 (328)

Efficient sequencing data compression and FPGA acceleration based on a two-step framework. [PDF]

Front Genet, 2023
Chen S, Chen Y, Wang Z, Qin W, Zhang J, Nand H, Zhang J, Li J, Zhang X, Liang X, Xu M.   +10 more
europepmc   +1 more source

Translating a Preclinically Tested 15 Hz rTMS Protocol to Humans With Chronic Spinal Cord Injury: A Safety and Feasibility Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Repetitive transcranial magnetic stimulation (rTMS) is a non‐invasive brain stimulation strategy with a demonstrated potential to reinforce the residual pathways after a spinal cord injury (SCI). A preclinically tested high‐frequency (15 Hz) rTMS (15 Hz rTMS) protocol was shown to induce corticospinal tract axon regeneration growth ...
Nabila Brihmat, Mehmed B. Bayram, Morgan Paine, Janelle Carnahan, Jian Zhong, Xiaofei Guan, Guang H. Yue, Soha Saleh, Gail F. Forrest   +8 more
wiley   +1 more source

Lossless Data Compression for Time-Series Sensor Data Based on Dynamic Bit Packing. [PDF]

Sensors (Basel), 2023
Hwang SH, Kim KM, Kim S, Kwak JW.
europepmc   +1 more source

Retracted: Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

Scalable NMF via linearly optimized data compression. [PDF]

Proc SPIE Int Soc Opt Eng, 2023
Ha SM, Bani A, Sotiras A.
europepmc   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

Precision requirements and data compression in CryoEM/CryoET. [PDF]

J Struct Biol, 2022
Fluty AC, Ludtke SJ.
europepmc   +1 more source

PREDICTIONS OF CONSTANT PRESSURE AND CONSTANT RATE F1LTRATIONS BASED UPON AN APPROXIMATE CORRECTION FOR SIDE WALL FRICTION IN COMPRESSION PERMEABILITY CELL DATA

, 1968
Mompei Shirato, Tsutomu Aragaki, Ryohei Mori, Kazuki SAWAMOTO   +3 more
openalex   +2 more sources

An improvement in the pointer coding of LZ77 data compression method [PDF]

, 1996
H. Yokoo
openalex   +1 more source

Neural Network Adaptive Control With Long Short‐Term Memory

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc, Abdullah Habboush, Yigit Gurses, Yildiray Yildiz, Anuradha M. Annaswamy   +4 more
wiley   +1 more source