FRACTAL COMPLEXITY-BASED FEATURE EXTRACTION ALGORITHM OF COMMUNICATION SIGNALS

An Interval-Based Algorithm for Feature Extraction from Speech Signals∗

Language disorders can be classified into the three linguistic levels of pronunciation, lexicon, and grammar. To identify the most important linguistic processes leading to disorders in the before-mentioned fields, both standardized test procedures and the analysis of freely spoken language are used in the everyday work of speech therapists. However, especially the analysis of freely spoken lan...

Low Complexity Feature Extraction for Classification of Harmonic Signals

A RELIEF Based Feature Extraction Algorithm

RELIEF is considered one of the most successful algorithms for assessing the quality of features due to its simplicity and effectiveness. It has been recently proved that RELIEF is an online algorithm that solves a convex optimization problem with a marginbased objective function. Starting from this mathematical interpretation, we propose a novel feature extraction algorithm, referred to as LFE...

Overlap-based feature weighting: The feature extraction of Hyperspectral remote sensing imagery

Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...

Exploratory Feature Extraction in Speech Signals

A novel unsupervised neural network for dimensionality reduction which seeks directions emphasizing multimodality is presented, and its connection to exploratory projection pursuit methods is discussed. This leads to a new statistical insight to the synaptic modification equations governing learning in Bienenstock, Cooper, and Munro (BCM) neurons (1982). The importance of a dimensionality reduc...