An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering

HMM-Based Acoustic Event Detection with AdaBoost Feature Selection

Because of the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature components in acoustic event detection. Based on these distances, we use AdaBoost to select a discriminant feature set and demonstrate that this feature set outperforms classical speech feature set such as MFCC in one-pas...

Adaptive Signal Detection in Auto-Regressive Interference with Gaussian Spectrum

A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...

Feature Selection for Multimodal Acoustic Event Detection

an analysis of persian phonology based on feature geometry framework

feature geometry, which is a basic assumption in current phonology, is concerned with the notion that the features are not an unstructured set, but are arranged hierarchically into a constituent structure tree. according to evidences in different languages, various models have been set forth on feature geometry framework. exploring persian phonological data and digging up evidences accordingly,...

A New Framework for Distributed Multivariate Feature Selection

Feature selection is considered as an important issue in classification domain. Selecting a good feature through maximum relevance criterion to class label and minimum redundancy among features affect improving the classification accuracy. However, most current feature selection algorithms just work with the centralized methods. In this paper, we suggest a distributed version of the mRMR featu...