AIMC Topic: Time Factors

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An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos.

Artificial intelligence in medicine
In assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, rates of live birth following clinical AR...

Pathological Voice Detection Based on Phase Reconstitution and Convolutional Neural Network.

Journal of voice : official journal of the Voice Foundation
The nonlinear dynamic features can effectively describe the acoustic characteristics of normal and pathological voice. In this paper, the phase space reconstruction and convolution neural network are used to classify the normal and pathological voice...

A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications.

Sensors (Basel, Switzerland)
Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or b...

Exponential Stability of Fractional-Order Switched Systems With Mode-Dependent Impulses and Its Application.

IEEE transactions on cybernetics
Most exiting results for impulsive switched systems (ISSs) are mainly built on the synchronous switching and impulses case; however, the impulses can not only occur in switched interval including switched instants but also the switched signals may ex...

New Global Asymptotic Robust Stability of Dynamical Delayed Neural Networks via Intervalized Interconnection Matrices.

IEEE transactions on cybernetics
This article identifies a new upper bound norm for the intervalized interconnection matrices pertaining to delayed dynamical neural networks under the parameter uncertainties. By formulating the appropriate Lyapunov functional and slope-bounded activ...

Improved Stability Criteria for Discrete-Time Delayed Neural Networks via Novel Lyapunov-Krasovskii Functionals.

IEEE transactions on cybernetics
This article investigates the stability problem for discrete-time neural networks with a time-varying delay by focusing on developing new Lyapunov-Krasovskii (L-K) functionals. A novel L-K functional is deliberately tailored from two aspects: 1) the ...

Stabilization via Event-Triggered Impulsive Control With Constraints for Switched Stochastic Systems.

IEEE transactions on cybernetics
This article studies the event-triggered impulsive control (ETIC) with constraints for the stabilization of switched stochastic systems (SSSs). An ETIC scheme with constraints is proposed for SSS by designing two levels of events via three indices: 1...

Delay Compensation-Based State Estimation for Time-Varying Complex Networks With Incomplete Observations and Dynamical Bias.

IEEE transactions on cybernetics
In this article, a delay-compensation-based state estimation (DCBSE) method is given for a class of discrete time-varying complex networks (DTVCNs) subject to network-induced incomplete observations (NIIOs) and dynamical bias. The NIIOs include the c...

Image-based time series forecasting: A deep convolutional neural network approach.

Neural networks : the official journal of the International Neural Network Society
Inspired by the successful use of deep learning in computer vision, in this paper we introduce ForCNN, a novel deep learning method for univariate time series forecasting that mixes convolutional and dense layers in a single neural network. Instead o...

DAFA-BiLSTM: Deep Autoregression Feature Augmented Bidirectional LSTM network for time series prediction.

Neural networks : the official journal of the International Neural Network Society
Time series forecasting models that use the past information of exogenous or endogenous sequences to forecast future series play an important role in the real world because most real-world time series datasets are rich in time-dependent information. ...