Search results for "Support Vector Machines"

showing 2 items of 22 documents

On the discrete linear ill‐posed problems

1999

An inverse problem of photo‐acoustic spectroscopy of semiconductors is investigated. The main problem is formulated as the integral equation of the first kind. Two different regularization methods are applied, the algorithms for defining regularization parameters are given. Diskrečiųjų blogai sąlygotų uždavinių klausimu Santrauka Darbe nagrinejamas foto‐akustines spektroskopijos puslaidininkiuose uždavinys, kuriame i vertinami nešeju difuzijos ir rekombinacijos procesai. Reikia atstatyti šaltinio funkcija f(x), jei žinoma antrosios eiles difuzijos lygtis ir atitinkamos kraštines salygos. Naudojantis matavimu, atliktu ivairiuose dažniuose, rezultatais sprendžiamas atvirkštinis uždavinys, kel…

Well-posed problemMathematical analysisRegularization perspectives on support vector machinesBackus–Gilbert method-Inverse problemIntegral equationRegularization (mathematics)Tikhonov regularizationModeling and SimulationInverse scattering problemQA1-939Applied mathematicsMathematicsAnalysisMathematicsMathematical Modelling and Analysis
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Signal processing techniques for robust sound event recognition

2019

The computational analysis of acoustic scenes is today a topic of major interest, with a growing community focused on designing machines capable of identifying and understanding the sounds produced in our environment, similar to how humans perform this task. Although these domains have not reached the industrial popularity of other related audio domains, such as speech recognition or music analysis, applications designed to identify the occurrence of sounds in a given scenario are rapidly increasing. These applications are usually limited to a set of sound classes, which must be defined beforehand. In order to train sound classification models, representative sets of sound events are record…

sound event recognitionfeature selection:CIENCIAS TECNOLÓGICAS [UNESCO]audio classificationdeep learningUNESCO::CIENCIAS TECNOLÓGICASsupport vector machines
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