METHOD OF PROCESSING VECTOR SIGNALS FOR PATTERN RECOGNITION BASED ON WAVELET ANALYSIS Russian patent published in 2019 - IPC G01N35/00 

Abstract RU 2690001 C1

FIELD: calculating; counting.

SUBSTANCE: invention relates to data processing methods. Method includes: A) primary processing of signal x(t), normalization of preprocessed signal to obtain array of signal samples to form training sample, divided into training, validation and test set; B) for each sample of sampling array, windows of current level of detail (WCLD) are determined, which correspond to specified value of width parameters s and position of their centers - t, with provision of overlapping of adjacent windows; C) each sample of sampling array is processed by wavelet transformation; D) selecting a reference function, a maximum number of its variables with subsequent construction of a family of models for displaying a wavelet coefficient function (a1…an) by one target value; E) after which each family model according to claim D) is trained on a training set with selection of weight parameters of models w1…wn and subsequent selection of the best models based on the criterion calculated on the validation set; F) checking selected models at step D) on a test sample by calculating an algorithm convergence evaluation criterion; G) selection of significant sections (SS) corresponding to windows of said level of detail, H) transition to the next level of detail inside selected by item G) SS - WCLD corresponding to better models containing wavelet coefficients ai, previously calculated inside these windows; I) for each windows of sections, determined at the first level of detail, applying a corresponding wavelet transformation with a smaller scale parameter to obtain a detailed representation of the set of SS, after which steps C)–I) are repeated until a convergence criterion is obtained, determined from the value of the target function on the test set, resulting in a set of paired combinations of s and t corresponding to the SS of the measured signal, from which the desired target parameter is determined.

EFFECT: technical result consists in improvement of target parameter determining accuracy.

17 cl, 3 dwg

Similar patents RU2690001C1

Title Year Author Number
METHOD AND SYSTEM OF THE FINAL AUTOMATOR FOR RECOGNIZING THE OPERATING STATE OF THE SENSOR 2018
  • Rueckert Frank
  • Weilbach Juliane
  • Nuernberg Frank-Thomas
RU2744908C1
METHOD FOR FORMING BRAIN-COMPUTER CONTROL SYSTEM 2019
  • Bobe Anatolij Sergeevich
  • Rashkov Grigorij Vadimovich
  • Fastovets Dmitrij Vladislavovich
RU2704497C1
METHOD AND SYSTEM FOR AUTOMATIC ECG ANALYSIS 2020
  • Egorov Konstantin Sergeevich
  • Avetisyan Manvel Sogomonovich
  • Sokolova Elena Vladimirovna
RU2767157C2
METHOD FOR AMALYZING MEDICAL DATA USING NEURAL NET LogNNet 2021
  • Velichko Andrei Aleksandrovich
  • Velichko Tatiana Vasilevna
RU2754723C1
METHOD OF DIAGNOSTICS OF LUNG CANCER BY ANALYSIS OF EXHALED AIR BY PATIENT ON THE BASIS OF ANALYSIS OF BIOELECTRIC POTENTIALS OF THE RAT OLFACTORY ANALYZER 2017
  • Medvedev Dmitrij Sergeevich
  • Kiroj Valerij Nikolaevich
  • Ilinykh Andrej Sergeevich
  • Shepelev Igor Evgenevich
  • Matukhno Aleksej Evgenevich
  • Smolikov Aleksej Borisovich
  • Zolotukhin Vladimir Vasilevich
  • Minyaeva Nadezhda Ruslanovna
RU2666873C1
METHOD OF NEURAL NETWORK FORECASTING OF CHANGE OF VALUES OF FUNCTION WITH ITS COMPLEMENTARY WAVELET PROCESSING AND DEVICE FOR ITS IMPLEMENTATION 2015
  • Belov Aleksej Anatolevich
  • Ermolaev Valerij Andreevich
  • Kropotov Yurij Anatolevich
  • Proskuryakov Aleksandr Yurevich
RU2600099C1
METHOD FOR DETECTING ANOMALOUS NETWORK TRAFFIC 2023
  • Zmitrovich Nikolaj Leonidovich
RU2811840C1
SPLICING SITES CLASSIFICATION BASED ON DEEP LEARNING 2018
  • Dzhaganatan, Kishor
  • Farkh, Kaj-Khou
  • Kiriazopulu Panajotopulu, Sofiya
  • Makrej, Dzheremi Frensis
RU2780442C2
METHOD OF BIOHYBRID SCREENING OF LUNG CANCER, STOMACH CANCER, DIABETES MELLITUS AND PULMONARY TUBERCULOSIS BY EXHALED AIR 2022
  • Sinyutina Olga Nikolaevna
  • Savolyuk Antonina Vasilevna
  • Mishin Nikita Aleksandrovich
  • Medvedev Dmitrij Sergeevich
RU2797334C1
METHOD FOR PREDICTING STICKING OF DRILLING PIPES IN PROCESS OF DRILLING BOREHOLE IN REAL TIME 2020
  • Shestakov Aleksandr Leonidovich
  • Kodirov Shakhboz Sharifovich
RU2753289C1

RU 2 690 001 C1

Authors

Efitorov Aleksandr Olegovich

Dolenko Sergej Anatolevich

Dates

2019-05-30Published

2017-12-29Filed