I. G. Persiantsev

发表

Diagnostic system for detection and analysis of auditory evoked potentials

Yu. V. Orlov, I. G. Persiantsev, S. P. Rebrik, 1995 .

Data-processing algorithms for automatic operation of ultrasonic systems with coherent data processing

Yu. V. Orlov, I. G. Persiantsev, V. G. Badalyan, 2004 .

A neural network algorithm for the prediction of events in multidimensional time series and its application to the analysis of data in cosmic physics

Yu. V. Orlov, I. G. Persiantsev, S. A. Dolenko, 2006, Pattern Recognition and Image Analysis.

Methods of input data compression in neural network solution of inverse problems of spectroscopy of multi-component solutions

I. G. Persiantsev, Alexander Efitorov, Sergey Dolenko, 2013 .

Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers

Yu. V. Orlov, I. G. Persiantsev, A. V. Dmitriev, 2001, Multiple Classifier Systems.

Neural network algorithms for analyzing multidimensional time series for predicting events and their application to study of Sun-Earth relations

Yu. V. Orlov, I. G. Persiantsev, S. A. Dolenko, 2007, Pattern Recognition and Image Analysis.

Neural Network Approaches to Solution of the Inverse Problem of Identification and Determination of Partial Concentrations of Salts in Multi-сomponent Water Solutions

I. G. Persiantsev, Alexander Efitorov, Sergey Burikov, 2014, ICANN.

Multi-stage Algorithm Based on Neural Network Committee for Prediction and Search for Precursors in Multi-dimensional Time Series

I. G. Persiantsev, S. A. Dolenko, Ju. S. Shugai, 2009, ICANN.

Use of neural network based auto-associative memory as a data compressor for pre-processing optical emission spectra in gas thermometry with the help of neural network

I. G. Persiantsev, Sergey Dolenko, A. V. Filippov, 2002 .

Application of artificial neural networks to solve problems of identification and determination of concentration of salts in multi-component water solutions by Raman spectra

I. G. Persiantsev, T. A. Dolenko, S. A. Dolenko, 2010, Optical Memory and Neural Networks.

Study of Influence of Parameter Grouping on the Error of Neural Network Solution of the Inverse Problem of Electrical Prospecting

I. G. Persiantsev, Igor Isaev, S. A. Dolenko, 2013, EANN.

A new implementation of the algorithm of adaptive construction of hierarchical neural network classifiers

I. G. Persiantsev, S. A. Dolenko, V. A. Svetlov, 2015, Optical Memory and Neural Networks.

Expert system for extraction of the evoked potentials

Yu. V. Orlov, I. G. Persiantsev, S. P. Rebrik, 1993 .

The use of artificial neural network segmentation of multivariate time series for the analysis of geomagnetic disturbances

I. G. Persiantsev, Sergey Dolenko, Irina N. Myagkova, 2016 .

Application of neural networks to fluorescent diagnostics of organic pollution in natural waters

Yu. V. Orlov, I. G. Persiantsev, S. P. Rebrik, 1992, [Proceedings] 1992 RNNS/IEEE Symposium on Neuroinformatics and Neurocomputers.

Application of neural networks to fluorescent diagnostics of organic pollution in natural waters

Yu. V. Orlov, I. G. Persiantsev, S. P. Rebrik, 1993, IEEE International Conference on Neural Networks.

Comparison of Input Data Compression Methods in Neural Network Solution of Inverse Problem in Laser Raman Spectroscopy of Natural Waters

I. G. Persiantsev, Sergey Burikov, Tatiana A. Dolenko, 2012, ICANN.

New opportunities in solution of inverse problems in laser spectroscopy due to application of artificial neural networks

I. G. Persiantsev, Viktor V. Fadeev, Tatiana A. Dolenko, 2002, International Conference on Coherent and Nonlinear Optics.

Horizon of Neural Network Prediction of Relativistic Electrons Flux in the Outer Radiation Belt of the Earth

I. G. Persiantsev, Vladimir Shiroky, Irina Myagkova, 2015, EANN '15.

Automatic Processing and Analysis of Sequential Images of the Sun

I. G. Persiantsev, Ju. S. Shugai, A. Y. Ryazanov, 2004, ICPR 2004.

Multifold Acceleration of Neural Network Computations Using GPU

I. G. Persiantsev, S. A. Dolenko, Alexander Guzhva, 2009, ICANN.

Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers

Yu. V. Orlov, Anthony G. Pipe, I. G. Persiantsev, 2001, FLAIRS Conference.

Self-organizing construction of hierarchical structure of multi-layer perceptrons

Yu. V. Orlov, I. G. Persiantsev, Sergey Dolenko, 1997 .

Construction of Hierarchical Neural Classifers by Self-Organizing Error Back-Propagation

Yu. V. Orlov, I. G. Persiantsev, S. A. Dolenko, 1998, NC.

Application of neural networks to fluorescent diagnostics of organic pollution in water

I. G. Persiantsev, S. P. Rebrik, Yuri N. Orlov, 1995, Other Conferences.

Solution of Inverse Problems in Laser Spectroscopy of Water Media with the Help of Neural Networks

I. G. Persiantsev, Brian Carse, Tatiana A. Dolenko, 2001, FLAIRS Conference.

The high-speed compression of large data streams in ultrasonic diagnostics

Yu. V. Orlov, I. G. Persiantsev, S. A. Sharov, 2006, Pattern Recognition and Image Analysis.

Benchmarking of Different Modifications of the Cascade Correlation Algorithm

Yu. V. Orlov, I. G. Persiantsev, Sergey Dolenko, 1998 .

Comparison of Adaptive Algorithms for Significant Feature Selection in Neural Network Based Solution of the Inverse Problem of Electrical Prospecting

I. G. Persiantsev, S. A. Dolenko, Alexander Guzhva, 2009, ICANN.

Neural Network Algorithm for Events Forecasting and Its Application to Space Physics Data

Yu. V. Orlov, I. G. Persiantsev, S. A. Dolenko, 2005, ICANN.

The applicability of wavelet transform to the extraction of informative features from the images of the Sun

I. G. Persiantsev, S. A. Dolenko, S. A. Sharov, 2006, Pattern Recognition and Image Analysis.

Neural Network Approaches to Solution of the Inverse Problem of Identification and Determination of the Ionic Composition of Multi-component Water Solutions

I. G. Persiantsev, Alexander Efitorov, Sergey Burikov, 2015, EANN.

Neural networks approach to discovering temporal correlations

I. G. Persiantsev, Sergey Dolenko, Ju. S. Shugai, 2003 .

New opportunity solutions to inverse problems in laser spectroscopy involving artificial neural networks

I. G. Persiantsev, Sergey Dolenko, Tatiana A. Dolenko, 2002 .

Adaptive methods for solving inverse problems in laser raman spectroscopy of multi-component solutions

I. G. Persiantsev, T. A. Dolenko, S. A. Burikov, 2012, Pattern Recognition and Image Analysis.

Comparison of the quality of solving the inverse problems of spectroscopy of multi-component solutions with neural network methods and with the method of projection to latent structures

I. G. Persiantsev, T. A. Dolenko, S. A. Burikov, 2015, Optical Memory and Neural Networks.