Results 61 to 70 of about 151,868 (248)

KL-Divergence Guided Two-Beam Viterbi Algorithm on Factorial HMMs [PDF]

, 2014
This thesis addresses the problem of the high computation complexity issue that arises when decoding hidden Markov models (HMMs) with a large number of states.
Yeh, Raymond
core   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source

GCRTcall: a transformer based basecaller for nanopore RNA sequencing enhanced by gated convolution and relative position embedding via joint loss training

Frontiers in Genetics
Nanopore sequencing, renowned for its ability to sequence DNA and RNA directly with read lengths extending to several hundred kilobases or even megabases, holds significant promise in fields like transcriptomics and other omics studies.
Qingwen Li, Qingwen Li, Chen Sun, Daqian Wang, Jizhong Lou, Jizhong Lou, Jizhong Lou   +6 more
doaj   +1 more source

Decoding Behavior Tasks From Brain Activity Using Deep Transfer Learning

IEEE Access, 2019
Recently, advances in noninvasive detection techniques have shown that it is possible to decode visual information from measurable brain activities. However, these studies typically focused on the mapping between neural activities and visual information,
Yufei Gao, Yameng Zhang, Hailing Wang, Xiaojuan Guo, Jiacai Zhang   +4 more
doaj   +1 more source

Predict or classify: The deceptive role of time-locking in brain signal classification

, 2016
Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision.
Rusconi, Marco, Valleriani, Angelo
core   +1 more source

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Proper account of auto-correlations improves decoding performances of state-space (semi) Markov models

Peer Community Journal
State-space models are widely used in ecology to infer hidden behaviors. This study develops an extensive numerical simulation-estimation experiment to evaluate the state decoding accuracy of four simple state-space models.
Bez, Nicolas, Gloaguen, Pierre, Etienne, Marie-Pierre, Lanco, Sophie, Joo, Rocío, Rivot, Etienne, Walker, Emily, Woillez, Mathieu, Mahévas, Stéphanie   +8 more
doaj   +1 more source

Hardware Based Projection onto The Parity Polytope and Probability Simplex

, 2016
This paper is concerned with the adaptation to hardware of methods for Euclidean norm projections onto the parity polytope and probability simplex. We first refine recent efforts to develop efficient methods of projection onto the parity polytope.
Draper, Stark C., Wasson, Mitchell
core   +1 more source

Pixelation‐Free, Monolithic Iontronic Pressure Sensors Enabling Large‐Area Simultaneous Pressure and Position Recognition via Machine Learning

Advanced Functional Materials, EarlyView.
A pixelation‐free, monolithic iontronic pressure sensor enables simultaneous pressure and position sensing over large areas. AC‐driven ion release generates spatially varying impedance pathways depending on the pressure. Machine learning algorithms effectively decouple overlapping pressure–position signals from the multichannel outputs, achieving high ...
Juhui Kim, Junseo Lee, Kwang‐Hun Choi, Seongil Im, Jae Hong Kim, Changsoon Choi, Junghwan Byun, Changhwan Shin, Ho Won Jang, Hyunsu Ju, Jung Ah Lim   +10 more
wiley   +1 more source

MSEI-ENet: A Multi-Scale EEG-Inception Integrated Encoder Network for Motor Imagery EEG Decoding

Brain Sciences
Background: Due to complex signal characteristics and distinct individual differences, the decoding of a motor imagery electroencephalogram (MI-EEG) is limited by the unsatisfactory performance of suboptimal traditional models.
Pengcheng Wu, Keling Fei, Baohong Chen, Lizheng Pan   +3 more
doaj   +1 more source