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Stochastic Processes

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Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

BMC systems biology
BACKGROUND: Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, mos...

Inferring MicroRNA Targets Based on Restricted Boltzmann Machines.

IEEE journal of biomedical and health informatics
Predicting the miRNA-target interactions (MTIs) is a critical task for elucidating mechanistic roles of miRNAs in pathophysiology. However, most existing techniques have a higher false positive because the precise miRNA target mechanisms are poorly k...

Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the globally exponential stability problem for a class of discrete-time stochastic memristive neural networks (DSMNNs) with both leakage delays as well as probabilistic time-varying delays. For the probabilistic delays, a...

Design of nonlinear optimal control for chaotic synchronization of coupled stochastic neural networks via Hamilton-Jacobi-Bellman equation.

Neural networks : the official journal of the International Neural Network Society
This paper presents a new theoretical design of nonlinear optimal control on achieving chaotic synchronization for coupled stochastic neural networks. To obtain an optimal control law, the proposed approach is developed rigorously by using Hamilton-J...

Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

Neural networks : the official journal of the International Neural Network Society
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Con...

Cooperating with machines.

Nature communications
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine coo...

H state estimation of stochastic memristor-based neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the problem of H state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into s...

How mimetic should a robotic fish be to socially integrate into zebrafish groups?

Bioinspiration & biomimetics
Biomimetic robots are promising tools in animal behavioural studies. If they are socially integrated in a group of animals, they can produce calibrated social stimuli to test the animal responses. However, the design of such social robots is challeng...

Transparent predictive modelling of the twin screw granulation process using a compensated interval type-2 fuzzy system.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
In this research, a new systematic modelling framework which uses machine learning for describing the granulation process is presented. First, an interval type-2 fuzzy model is elicited in order to predict the properties of the granules produced by t...

pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues o...