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Stochastic Processes

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Deep learning for computational structural optimization.

ISA transactions
We investigate a novel computational approach to computational structural optimization based on deep learning. After employing algorithms to solve the stiffness formulation of structures, we used their improvement to optimize the structural computati...

Segmentation of prostate and prostate zones using deep learning : A multi-MRI vendor analysis.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: Develop a deep-learning-based segmentation algorithm for prostate and its peripheral zone (PZ) that is reliable across multiple MRI vendors.

Human respiration monitoring using infrared thermography and artificial intelligence.

Biomedical physics & engineering express
The respiration rate (RR) is the most vital parameter used for the determination of human health. The most widely adopted techniques, used to monitor the RR are contact in nature and face many drawbacks. This paper reports the use of Infrared Thermog...

Molecular and DNA Artificial Neural Networks via Fractional Coding.

IEEE transactions on biomedical circuits and systems
This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using f...

Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the anti-synchronization issue for stochastic delayed reaction-diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presenc...

Improved value iteration for neural-network-based stochastic optimal control design.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel value iteration adaptive dynamic programming (ADP) algorithm is presented, which is called an improved value iteration ADP algorithm, to obtain the optimal policy for discrete stochastic processes. In the improved value iterati...

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory foot...

Cluster stochastic synchronization of complex dynamical networks via fixed-time control scheme.

Neural networks : the official journal of the International Neural Network Society
By means of fixed-time (FDT) control technique, cluster stochastic synchronization of complex networks (CNs) is investigated. Quantized controller is designed to realize the synchronization of CNs within a settling time. FDT synchronization criteria ...

Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data.

International journal of molecular sciences
Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct ...

Finite-time and fixed-time anti-synchronization of Markovian neural networks with stochastic disturbances via switching control.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a unified theoretical framework to study the problem of finite/fixed-time drive-response anti-synchronization for a class of Markovian stochastic neural networks. State feedback switching controllers without the sign function are ...