Custom IP cores for robust data analysis and pattern recognition algorithms used in gas applications

The package of applied programs named KVAZAR has been elaborated to be used for classification, diagnostic, predicative, experimental data analysis problems. The package may be used in medicine, biology, geology, economics, engineering and some other problems. The algorithmical base of the package is the method of pattern recognition, based on the linear inequalities and committee constructions. Other algorithms are used too. The package KVAZAR is intended to be used with IBM PC AT/XT. The range of processing data is bounded by 40,000 numbers.

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Multiclass Decision Forest—A Novel Pattern Recognition Method for Multiclass Classification in Microarray Data Analysis

DNA and Cell Biology ◽

10.1089/dna.2004.23.685 ◽

2004 ◽

Vol 23 (10) ◽

pp. 685-694 ◽

Cited By ~ 30

Author(s):

Huixiao Hong ◽

Weida Tong ◽

Roger Perkins ◽

Hong Fang ◽

Qian Xie ◽

...

Keyword(s):

Pattern Recognition ◽

Data Analysis ◽

Microarray Data ◽

Multiclass Classification ◽

Microarray Data Analysis ◽

Pattern Recognition Method ◽

Recognition Method ◽

Decision Forest

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The Often-Overlooked Power of Summary Statistics in Exploratory Data Analysis: Comparison of Pattern Recognition Entropy (PRE) to Other Summary Statistics and Introduction of Divided Spectrum-PRE (DS-PRE)

Journal of Chemical Information and Modeling ◽

10.1021/acs.jcim.1c00244 ◽

2021 ◽

Vol 61 (9) ◽

pp. 4173-4189

Author(s):

Tahereh G. Avval ◽

Behnam Moeini ◽

Victoria Carver ◽

Neal Fairley ◽

Emily F. Smith ◽

...

Keyword(s):

Pattern Recognition ◽

Data Analysis ◽

Exploratory Data Analysis ◽

Summary Statistics ◽

Exploratory Data

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Application of image enhancement and pattern recognition algorithms to seismic reflection data

Bulletin of the Seismological Society of America ◽

10.1785/bssa0730010307 ◽

1983 ◽

Vol 73 (1) ◽

pp. 307-314

Author(s):

George A. McMechan

Keyword(s):

Pattern Recognition ◽

Pacific Ocean ◽

Image Enhancement ◽

Seismic Reflection ◽

Gray Scale ◽

Seismic Reflection Data ◽

Reflection Data ◽

Recognition Algorithms ◽

Gray Scale Image ◽

Northeastern Pacific

abstract A digital seismic reflection section may be converted to a gray scale image composed of pixels and processed with techniques borrowed from the disciplines of image enhancement and pattern recognition. Types of processing include scaling, thresholding, density equalization, filtering, segmentation, and edge-finding. These are successfully applied to a migrated common mid-point seismic reflection line that traverses the Queen Charlotte fault (located in the northeastern Pacific Ocean). The result is the definition and enhancement of an elongated, near-vertical reflectivity anomaly associated with the Queen Charlotte fault.

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